From aeec31403d05c32dea5a8181cd4dd65df14d1242 Mon Sep 17 00:00:00 2001
From: Shreyanand <shanand@redhat.com>
Date: Fri, 28 Apr 2023 13:25:15 +0000
Subject: [PATCH] Add notebook with gpu footprint

Update Pipfile

Update Readme
---
 Pipfile                       |   12 +-
 Pipfile.lock                  | 2089 ++++++++++++++++++++-------------
 notebooks/README.md           |    1 +
 notebooks/gpu-footprint.ipynb |  352 ++++++
 4 files changed, 1637 insertions(+), 817 deletions(-)
 create mode 100755 notebooks/gpu-footprint.ipynb

diff --git a/Pipfile b/Pipfile
index f9e6cbd..b780e95 100644
--- a/Pipfile
+++ b/Pipfile
@@ -9,16 +9,24 @@ coverage = "*"
 Sphinx = "*"
 
 [packages]
+ipywidgets = "*"
+ipynb = "*"
+boto3 = "*"
+python-dotenv = "*"
+langchain = "*"
+transformers = "*"
+torch = "*"
+unstructured = "*"
+GPUtil = "*" 
+numba = "*"
 awscli = "*"
 pypdf2 = "*"
 nltk = "*"
 rouge = "*"
 jiwer = "*"
 evaluate = "*"
-langchain = "*"
 openai = "*"
 chromadb = "*"
-unstructured = "*"
 bert-score = "*"
 
 [requires]
diff --git a/Pipfile.lock b/Pipfile.lock
index e73710b..dda1096 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "5422988f112770d9fc019754ffeaaddd215e0a4ec03eef8cb816e9d74fe4c2c2"
+            "sha256": "9c4154ac41ee3638208cf5078388d69e2d7863890249badf1fa1d19819916fc1"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -106,6 +106,7 @@
                 "sha256:fe11310ae1e4cd560035598c3f29d86cef39a83d244c7466f95c27ae04850f10",
                 "sha256:fe7ba4a51f33ab275515f66b0a236bcde4fb5561498fe8f898d4e549b2e4509f"
             ],
+            "markers": "python_version >= '3.6'",
             "version": "==3.8.4"
         },
         "aiosignal": {
@@ -126,42 +127,56 @@
         },
         "argilla": {
             "hashes": [
-                "sha256:b18601c7ef1af0f7e7a3b825ee8d63653d5db66a954a20bad1b3e6a8aab56969",
-                "sha256:bbbed0b45c240dfee622af5f8e33623400f6a681407c6aa77f68489d52672ec8"
+                "sha256:096325b15d2525519277f70904ea9d526347b4dcafec5257d5cfed617b99cdbd",
+                "sha256:4b7f9b56516130ab9d63b3106a244a226506b3109fdaaac0d4829f46d2225fb6"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==1.4.0"
+            "version": "==1.6.0"
+        },
+        "asttokens": {
+            "hashes": [
+                "sha256:4622110b2a6f30b77e1473affaa97e711bc2f07d3f10848420ff1898edbe94f3",
+                "sha256:6b0ac9e93fb0335014d382b8fa9b3afa7df546984258005da0b9e7095b3deb1c"
+            ],
+            "version": "==2.2.1"
         },
         "async-timeout": {
             "hashes": [
                 "sha256:2163e1640ddb52b7a8c80d0a67a08587e5d245cc9c553a74a847056bc2976b15",
                 "sha256:8ca1e4fcf50d07413d66d1a5e416e42cfdf5851c981d679a09851a6853383b3c"
             ],
-            "markers": "python_version >= '3.6'",
+            "markers": "python_version < '3.11'",
             "version": "==4.0.2"
         },
         "attrs": {
             "hashes": [
-                "sha256:29e95c7f6778868dbd49170f98f8818f78f3dc5e0e37c0b1f474e3561b240836",
-                "sha256:c9227bfc2f01993c03f68db37d1d15c9690188323c067c641f1a35ca58185f99"
+                "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04",
+                "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"
             ],
-            "markers": "python_version >= '3.6'",
-            "version": "==22.2.0"
+            "markers": "python_version >= '3.7'",
+            "version": "==23.1.0"
         },
         "awscli": {
             "hashes": [
-                "sha256:89654aef9589465618470f7c49d33962ee2af4c46ed472395adff517c604587f",
-                "sha256:ed29786daa670ce3580999ec29b5cb27093b94c12f488f9a0d87c6982a7d95f9"
+                "sha256:4db7e252f910f64a74b21f969e5c5f526144b7ca236d76e6cc68a21c4fc7bbbf",
+                "sha256:a7000baa0942c1e621339aa1abd36fff2d4fbfc42490d3333f85e949d4f67af8"
             ],
             "index": "pypi",
-            "version": "==1.27.95"
+            "version": "==1.27.122"
+        },
+        "backcall": {
+            "hashes": [
+                "sha256:5cbdbf27be5e7cfadb448baf0aa95508f91f2bbc6c6437cd9cd06e2a4c215e1e",
+                "sha256:fbbce6a29f263178a1f7915c1940bde0ec2b2a967566fe1c65c1dfb7422bd255"
+            ],
+            "version": "==0.2.0"
         },
         "backoff": {
             "hashes": [
                 "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba",
                 "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"
             ],
-            "markers": "python_version >= '3.7' and python_version < '4'",
+            "markers": "python_version >= '3.7' and python_version < '4.0'",
             "version": "==2.2.1"
         },
         "bert-score": {
@@ -172,13 +187,21 @@
             "index": "pypi",
             "version": "==0.3.13"
         },
+        "boto3": {
+            "hashes": [
+                "sha256:38ca632be379963f2a2749b5f63a81fe1679913b954914f470ad282c77674bbc",
+                "sha256:4d575c180312bec6108852bae12e6396b9d1bb404154d652c57ee849c62fbb83"
+            ],
+            "index": "pypi",
+            "version": "==1.26.122"
+        },
         "botocore": {
             "hashes": [
-                "sha256:5f5f1c8125f8c331f561ca0a7a892f709df206714c306c48fd907eee469926cb",
-                "sha256:e9ffd4a2fc415c313eda03713c212e3121084fdcb21e20aac5b15924a4ae5a9d"
+                "sha256:9e4984a9e9777c6b949aa1e98323fa35480d9f99d447af7e179ae611f7ed5af9",
+                "sha256:c3b41078d235761b9c5dc22f534a76952622ef96787b96bbd10242ec4d73f2a5"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==1.29.95"
+            "version": "==1.29.122"
         },
         "certifi": {
             "hashes": [
@@ -266,16 +289,16 @@
                 "sha256:f8303414c7b03f794347ad062c0516cee0e15f7a612abd0ce1e25caf6ceb47df",
                 "sha256:fca62a8301b605b954ad2e9c3666f9d97f63872aa4efcae5492baca2056b74ab"
             ],
-            "markers": "python_version >= '3.7'",
+            "markers": "python_full_version >= '3.7.0'",
             "version": "==3.1.0"
         },
         "chromadb": {
             "hashes": [
-                "sha256:0098be00ac3cec50482af6a9c2e44d62c5f8ad10143affc0893599a936ce1769",
-                "sha256:ad7d267db306e09b6647ae8b9d2a58a3d3c245a8609cb3e803d49d6789e1111d"
+                "sha256:7b3417892666dc90df10eafae719ee189037c448c1c96e6c7964daa870483c3a",
+                "sha256:b497516ef403d357944742b2363eb729019d68ec0d1a7062a6abe8e127ccf28f"
             ],
             "index": "pypi",
-            "version": "==0.3.11"
+            "version": "==0.3.21"
         },
         "click": {
             "hashes": [
@@ -287,96 +310,96 @@
         },
         "clickhouse-connect": {
             "hashes": [
-                "sha256:00ebb87f462cbdc277fb3e5cb0c1d42811bf43424e7131bafdac1f54d268c56c",
-                "sha256:07edcc3147245c535b9c4fc38e06c0f8fb027def1525880dc7119039bb582837",
-                "sha256:0c9ee4bf80a5ba3bbab659b0984d2ad67cc1fbdff36cb02e6f2e465bffef3012",
-                "sha256:1a006950a2804fef14b392456dca3465573a88ad5d96f8c42f8613532ca7b681",
-                "sha256:1c222fe85f641f58a822d232c5cc2678894c84c7bdb0ad13ba77e58ee27e2c9a",
-                "sha256:2050780aabfe6297dd434e07e2122924262584b6b2a0caec12944d44e64d14f4",
-                "sha256:23cdb94e729a8718239e7213b0c02e6134c97e68014a7215e4d4147a3e882345",
-                "sha256:24cc51f65b4c93ced3f355928089ee59d66c63ea590a2f4e6a366c943b05b7cb",
-                "sha256:257fbeb8de5c76088a71fdf5e16e2d08b366e08c15a500a8ad77b083614fc9d0",
-                "sha256:282f09e86357b1bcdbcefbe9a43ef12e615635f7209b1d76376e511257864146",
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-            "version": "==0.5.16"
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+                "sha256:e0ed796530641c8a21a423f9bb7882117dbbeee11ec78dbc335402a678d937ae"
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         "colorama": {
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@@ -386,6 +409,14 @@
             "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'",
             "version": "==0.4.4"
         },
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+                "sha256:a61efa9daffcfbe66fd643ba966f846a624e4e6d6767eda9cf6e993aadaab93e"
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+            "version": "==0.1.3"
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                 "sha256:452f9dc859be7f06631ddcb328b6919c67984aca654e5fefb3914d54691aed60",
@@ -472,11 +503,43 @@
         },
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-                "sha256:e2764c90aa3af96450a9747a934b8893b121f79f58d89e123cb1a7046bb8e81e"
+                "sha256:0a23bdf1fc28d82dd496375289d72f7917d149a95062ab2647cf621d67ed74ca",
+                "sha256:faf164c18a41bea51df3f369e872f8be5b84c12ea5f6393c3896f56038af1ea3"
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+            "markers": "python_full_version >= '3.7.0'",
+            "version": "==2.12.0"
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+                "sha256:279d64c408c60431c8ee832dfd9ace7c396984fd7341fa3116aee414e7dcd88d",
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+                "sha256:b3e7ac809b991006ad7f857f016fa92014445085711ef111fdc3f74f66144096",
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+                "sha256:c0ff93ae90a03b06d85b2c529eca51ab15457868a377c4cc40a23ab0e4e552a3",
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+                "sha256:d71b31117779d9a90b745720c0eab54ae1da76d5b38c8026c654f4a066b0130a",
+                "sha256:dbe04e7568aa69361a5b4c47b4493d5680bfa3a911d1e105fbea1b1f23f3eb45",
+                "sha256:de86029696e1b3b4d0d49076b9eba606c226e33ae312a57a46dca14ff370894d",
+                "sha256:e3876611d114a18aafef6383695dfc3f1217c98a9168c1aaf1a02b01ec7d8d1e",
+                "sha256:ed6d5413474e209ba50b1a75b2d9eecf64d41e6e4501977991cdc755dc83ab0f",
+                "sha256:f90a2d4ad9a035cee7331c06a4cf2245e38bd7c89554fe3b616d90ab8aab89cc"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==2.10.1"
+            "version": "==1.6.7"
+        },
+        "decorator": {
+            "hashes": [
+                "sha256:637996211036b6385ef91435e4fae22989472f9d571faba8927ba8253acbc330",
+                "sha256:b8c3f85900b9dc423225913c5aace94729fe1fa9763b38939a95226f02d37186"
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+            "version": "==5.1.1"
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         "deprecated": {
             "hashes": [
@@ -570,29 +633,36 @@
             "index": "pypi",
             "version": "==0.4.0"
         },
+        "executing": {
+            "hashes": [
+                "sha256:0314a69e37426e3608aada02473b4161d4caf5a4b244d1d0c48072b8fee7bacc",
+                "sha256:19da64c18d2d851112f09c287f8d3dbbdf725ab0e569077efb6cdcbd3497c107"
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+            "version": "==1.2.0"
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         "fastapi": {
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-                "sha256:daf73bbe844180200be7966f68e8ec9fd8be57079dff1bacb366db32729e6eb5"
+                "sha256:9569f0a381f8a457ec479d90fa01005cfddaae07546eb1f3fa035bc4797ae7d5",
+                "sha256:a870d443e5405982e1667dfe372663abf10754f246866056336d7f01c21dab07"
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             "markers": "python_version >= '3.7'",
-            "version": "==0.95.0"
+            "version": "==0.95.1"
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         "filelock": {
             "hashes": [
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-                "sha256:e90b34656470756edf8b19656785c5fea73afa1953f3e1b0d645cef11cab3182"
+                "sha256:ad98852315c2ab702aeb628412cbf7e95b7ce8c3bf9565670b4eaecf1db370a9",
+                "sha256:fc03ae43288c013d2ea83c8597001b1129db351aad9c57fe2409327916b8e718"
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             "markers": "python_version >= '3.7'",
-            "version": "==3.10.0"
+            "version": "==3.12.0"
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         "fonttools": {
             "hashes": [
-                "sha256:85245aa2fd4cf502a643c9a9a2b5a393703e150a6eaacc3e0e84bb448053f061",
-                "sha256:e2d9f10337c9e3b17f9bce17a60a16a885a7d23b59b7f45ce07ea643e5580439"
+                "sha256:64c0c05c337f826183637570ac5ab49ee220eec66cf50248e8df527edfa95aeb",
+                "sha256:9234b9f57b74e31b192c3fc32ef1a40750a8fbc1cd9837a7b7bfc4ca4a5c51d7"
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             "markers": "python_version >= '3.8'",
-            "version": "==4.39.2"
+            "version": "==4.39.3"
         },
         "frozenlist": {
             "hashes": [
@@ -679,11 +749,18 @@
                 "http"
             ],
             "hashes": [
-                "sha256:24e635549a590d74c6c18274ddd3ffab4753341753e923408b1904eaabafe04d",
-                "sha256:bf57215e19dbfa4fe7edae53040cc1deef825e3b1605cca9a8d2c2fadd2328a0"
+                "sha256:bf064186cd8808f0b2f6517273339ba0a0c8fb1b7048991c28bc67f58b8b67cd",
+                "sha256:f398de9b49b14e9d84d2c2d11b7b67121bc072fe97b930c4e5668ac3917d8307"
             ],
             "markers": "python_version >= '3.8'",
-            "version": "==2023.3.0"
+            "version": "==2023.4.0"
+        },
+        "gputil": {
+            "hashes": [
+                "sha256:099e52c65e512cdfa8c8763fca67f5a5c2afb63469602d5dcb4d296b3661efb9"
+            ],
+            "index": "pypi",
+            "version": "==1.4.0"
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         "greenlet": {
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@@ -748,7 +825,7 @@
                 "sha256:f82d4d717d8ef19188687aa32b8363e96062911e63ba22a0cff7802a8e58e5f1",
                 "sha256:fc3a569657468b6f3fb60587e48356fe512c1754ca05a564f11366ac9e306526"
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-            "markers": "python_version >= '3' and platform_machine == 'aarch64' or (platform_machine == 'ppc64le' or (platform_machine == 'x86_64' or (platform_machine == 'amd64' or (platform_machine == 'AMD64' or (platform_machine == 'win32' or platform_machine == 'WIN32')))))",
+            "markers": "platform_machine == 'aarch64' or (platform_machine == 'ppc64le' or (platform_machine == 'x86_64' or (platform_machine == 'amd64' or (platform_machine == 'AMD64' or (platform_machine == 'win32' or platform_machine == 'WIN32')))))",
             "version": "==2.0.2"
         },
         "h11": {
@@ -829,11 +906,11 @@
         },
         "huggingface-hub": {
             "hashes": [
-                "sha256:1f95f65c5e7aa76728701402f55b697ee8a8b50234adda91fbdbb81038fbcd21",
-                "sha256:f73a298a55028575334f9670d86b8171a4dd890b320315f3ad28a20b9eb3b5bc"
+                "sha256:9ab899af8e10922eac65e290d60ab956882ab0bf643e3d990b1394b6b47b7fbc",
+                "sha256:9fc619170d800ff3793ad37c9757c255c8783051e1b5b00501205eb43ccc4f27"
             ],
-            "markers": "python_version >= '3.7'",
-            "version": "==0.13.3"
+            "markers": "python_full_version >= '3.7.0'",
+            "version": "==0.14.1"
         },
         "idna": {
             "hashes": [
@@ -845,11 +922,11 @@
         },
         "importlib-metadata": {
             "hashes": [
-                "sha256:43ce9281e097583d758c2c708c4376371261a02c34682491a8e98352365aad20",
-                "sha256:ff80f3b5394912eb1b108fcfd444dc78b7f1f3e16b16188054bd01cb9cb86f09"
+                "sha256:43dd286a2cd8995d5eaef7fee2066340423b818ed3fd70adf0bad5f1fac53fed",
+                "sha256:92501cdf9cc66ebd3e612f1b4f0c0765dfa42f0fa38ffb319b6bd84dd675d705"
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             "markers": "python_version < '3.10'",
-            "version": "==6.1.0"
+            "version": "==6.6.0"
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         "importlib-resources": {
             "hashes": [
@@ -859,6 +936,46 @@
             "markers": "python_version < '3.10'",
             "version": "==5.12.0"
         },
+        "ipykernel": {
+            "hashes": [
+                "sha256:1ae6047c1277508933078163721bbb479c3e7292778a04b4bacf0874550977d6",
+                "sha256:302558b81f1bc22dc259fb2a0c5c7cf2f4c0bdb21b50484348f7bafe7fb71421"
+            ],
+            "markers": "python_version >= '3.8'",
+            "version": "==6.22.0"
+        },
+        "ipynb": {
+            "hashes": [
+                "sha256:8d834c777ca3885289938728cc382f081c86a58e92961e86f0aba60c96938ce5",
+                "sha256:9686aafce6fd58ec160fa6ba649a7810df89cc0f06a317188ac5e59fd728e325"
+            ],
+            "index": "pypi",
+            "version": "==0.5.1"
+        },
+        "ipython": {
+            "hashes": [
+                "sha256:8d56026b882958db8eab089654f0c045d1237622313a1506da136fb0cce4270f",
+                "sha256:a0a8a30376cee8019c6e22bc0ab4320762f5f5e4d7abed0ea3ee4b95e3982ad5"
+            ],
+            "markers": "python_version >= '3.8'",
+            "version": "==8.13.0"
+        },
+        "ipywidgets": {
+            "hashes": [
+                "sha256:a60bf8d2528997e05ac83fd19ea2fbe65f2e79fbe1b2b35779bdfc46c2941dcc",
+                "sha256:de7d779f2045d60de9f6c25f653fdae2dba57898e6a1284494b3ba20b6893bb8"
+            ],
+            "index": "pypi",
+            "version": "==8.0.6"
+        },
+        "jedi": {
+            "hashes": [
+                "sha256:203c1fd9d969ab8f2119ec0a3342e0b49910045abe6af0a3ae83a5764d54639e",
+                "sha256:bae794c30d07f6d910d32a7048af09b5a39ed740918da923c6b780790ebac612"
+            ],
+            "markers": "python_version >= '3.6'",
+            "version": "==0.18.2"
+        },
         "jinja2": {
             "hashes": [
                 "sha256:31351a702a408a9e7595a8fc6150fc3f43bb6bf7e319770cbc0db9df9437e852",
@@ -869,11 +986,11 @@
         },
         "jiwer": {
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-                "sha256:cb6d6bfbb0c630dab49d3828f17873dd1dfbd2f7c0bcf26c1092f4e6eaa68062",
-                "sha256:d6f51a9c90270503545c6fdd38815b41e2ef240a450541994b089c50242b33c2"
+                "sha256:33d552094a6dfb072ef91d34bf3edb57eac94c9c35399d71062bf23b2c46c631",
+                "sha256:425448ae5eacc3a49d6fe243ecb5bca5d6101fca07406d93166265c3105744e5"
             ],
             "index": "pypi",
-            "version": "==3.0.0"
+            "version": "==3.0.1"
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         "jmespath": {
             "hashes": [
@@ -891,6 +1008,30 @@
             "markers": "python_version >= '3.7'",
             "version": "==1.2.0"
         },
+        "jupyter-client": {
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@@ -967,17 +1108,51 @@
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@@ -1105,11 +1280,11 @@
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@@ -1229,6 +1404,14 @@
             "markers": "python_version >= '3.8'",
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@@ -1243,6 +1426,14 @@
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@@ -1351,13 +1542,21 @@
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@@ -1367,6 +1566,76 @@
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@@ -1398,7 +1667,7 @@
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@@ -1490,13 +1759,28 @@
             "markers": "platform_system == 'Linux' and platform_machine == 'x86_64'",
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@@ -1508,11 +1792,11 @@
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@@ -1547,88 +1831,157 @@
             "markers": "python_version >= '3.8'",
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@@ -2346,7 +2769,7 @@
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@@ -2358,19 +2781,40 @@
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@@ -2379,13 +2823,21 @@
             "markers": "python_version >= '3.7'",
             "version": "==4.65.0"
         },
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@@ -2428,10 +2880,11 @@
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@@ -2446,11 +2899,11 @@
                 "standard"
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@@ -2489,100 +2942,112 @@
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             "markers": "python_version >= '3.7'",
             "version": "==0.40.0"
         },
+        "widgetsnbextension": {
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+                "sha256:864e36947289be05abd83267c4bade35e772526d3e9653444a9dc891faf0d698",
+                "sha256:8769a67e8816c7e94d5bf446fc0501641fde78fdff362feb28c2c64d45d0e9b1",
+                "sha256:876e4ef3eff00b50787867c5bae84857a9af4c369a9d5b266cd9b19f61e48ef7",
+                "sha256:89e63b38c7b888e00fd42ce458f838dccb66de06baea2da71801b0fc9070bfa0",
+                "sha256:92b565c51732ea2e7e541709ccce76391b39f4254260e5922e08e00971e88e33",
+                "sha256:9e5eedde6e6e241ec3816f05767cc77e7456bf5ec6b373fb29917f0990e2078f",
+                "sha256:a5c4f2e44a2ae15fa6883898e756552db5105ca4bd918634cbd5b7c00e19e8a1",
+                "sha256:ab08af91cf4d847a6e15d7d5eeae5fead1487caf16ff3a2056dbe64d058fd246",
+                "sha256:ab08e03add2cf5793e66ac1bbbb24acfa90c125476f5724f5d44c56eeec1d635",
+                "sha256:ac4861241e693e21b280f07844ae0e0707665e1dfcbf9466b793584984ae45c4",
+                "sha256:b3023ce23e41a6f006c09f7e6d62b6c069c36bdc9f7de16a5ef823acc02e6c63",
+                "sha256:bc47015fc0455753e8aba1f38b81b731aaf7f004a0c390b404e0fcf1d6c1d72f",
+                "sha256:c2becddfcbf3d994a8f4f9dd2b6015cae3a3eff50dedc6e4a17c3cccbe8f93d4",
+                "sha256:cdee9a77fd0ce000781680b6a1f4b721c567f66f2f73a49be1843ff439d634f3",
+                "sha256:cdfb53bef4b2739ff747ebbd76d6ac5384371fd3c7a8af08899074eba034d483",
+                "sha256:d4db4e6c115d869cd5397d3d21fd99e4c7053205c33a4ae725c90d19dcd178af",
+                "sha256:d9f770c6052d9b5c9b0e824fd8c003fe33276473b65b4f10ece9565ceb62438e",
+                "sha256:e41a7f44e73b37c6f0132ecfdc1c8b67722f42a3d9b979e6ebc150c8e80cf13a",
+                "sha256:ea534200efbf600e60130c48552f99f351cae2906898a9cd924c1c7f2fb02853",
+                "sha256:f19ba9301e6fb0b94ba71fda9a1b02d11f0aab7f8e2455122a4e2921b6703c2f",
+                "sha256:f37ae1804596f13d811e0247ffc8219f5261b3565bdf45fcbb4fc091b8e9ff35",
+                "sha256:f7668a621afc52db29f6867e0e9c72a1eec9f02c94a7c36599119d557cf6e471",
+                "sha256:f7ffdb3af2a01ce91577f84fc0faa056029fe457f3183007cffe7b11ea78b23c",
+                "sha256:fabd1f4d12dfd6b4f309208c2f31b116dc5900e0b42dbafe4ee1bc7c998ffbb0"
             ],
             "index": "pypi",
-            "version": "==7.2.2"
+            "version": "==7.2.4"
         },
         "docutils": {
             "hashes": [
@@ -3117,11 +3582,11 @@
         },
         "importlib-metadata": {
             "hashes": [
-                "sha256:43ce9281e097583d758c2c708c4376371261a02c34682491a8e98352365aad20",
-                "sha256:ff80f3b5394912eb1b108fcfd444dc78b7f1f3e16b16188054bd01cb9cb86f09"
+                "sha256:43dd286a2cd8995d5eaef7fee2066340423b818ed3fd70adf0bad5f1fac53fed",
+                "sha256:92501cdf9cc66ebd3e612f1b4f0c0765dfa42f0fa38ffb319b6bd84dd675d705"
             ],
             "markers": "python_version < '3.10'",
-            "version": "==6.1.0"
+            "version": "==6.6.0"
         },
         "jinja2": {
             "hashes": [
@@ -3197,11 +3662,11 @@
         },
         "packaging": {
             "hashes": [
-                "sha256:714ac14496c3e68c99c29b00845f7a2b85f3bb6f1078fd9f72fd20f0570002b2",
-                "sha256:b6ad297f8907de0fa2fe1ccbd26fdaf387f5f47c7275fedf8cce89f99446cf97"
+                "sha256:994793af429502c4ea2ebf6bf664629d07c1a9fe974af92966e4b8d2df7edc61",
+                "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==23.0"
+            "version": "==23.1"
         },
         "pycodestyle": {
             "hashes": [
@@ -3221,25 +3686,19 @@
         },
         "pygments": {
             "hashes": [
-                "sha256:b3ed06a9e8ac9a9aae5a6f5dbe78a8a58655d17b43b93c078f094ddc476ae297",
-                "sha256:fa7bd7bd2771287c0de303af8bfdfc731f51bd2c6a47ab69d117138893b82717"
+                "sha256:8ace4d3c1dd481894b2005f560ead0f9f19ee64fe983366be1a21e171d12775c",
+                "sha256:db2db3deb4b4179f399a09054b023b6a586b76499d36965813c71aa8ed7b5fd1"
             ],
-            "markers": "python_version >= '3.6'",
-            "version": "==2.14.0"
-        },
-        "pytz": {
-            "hashes": [
-                "sha256:01a0681c4b9684a28304615eba55d1ab31ae00bf68ec157ec3708a8182dbbcd0",
-                "sha256:78f4f37d8198e0627c5f1143240bb0206b8691d8d7ac6d78fee88b78733f8c4a"
-            ],
-            "version": "==2022.7.1"
+            "markers": "python_version >= '3.7'",
+            "version": "==2.15.1"
         },
         "requests": {
             "hashes": [
-                "sha256:64299f4909223da747622c030b781c0d7811e359c37124b4bd368fb8c6518baa",
-                "sha256:98b1b2782e3c6c4904938b84c0eb932721069dfdb9134313beff7c83c2df24bf"
+                "sha256:e8f3c9be120d3333921d213eef078af392fba3933ab7ed2d1cba3b56f2568c3b",
+                "sha256:f2e34a75f4749019bb0e3effb66683630e4ffeaf75819fb51bebef1bf5aef059"
             ],
-            "version": "==2.28.2"
+            "markers": "python_version >= '3.7'",
+            "version": "==2.29.0"
         },
         "snowballstemmer": {
             "hashes": [
@@ -3250,11 +3709,11 @@
         },
         "sphinx": {
             "hashes": [
-                "sha256:0dac3b698538ffef41716cf97ba26c1c7788dba73ce6f150c1ff5b4720786dd2",
-                "sha256:807d1cb3d6be87eb78a381c3e70ebd8d346b9a25f3753e9947e866b2786865fc"
+                "sha256:6d56a34697bb749ffa0152feafc4b19836c755d90a7c59b72bc7dfd371b9cc6b",
+                "sha256:97787ff1fa3256a3eef9eda523a63dbf299f7b47e053cfcf684a1c2a8380c912"
             ],
             "index": "pypi",
-            "version": "==6.1.3"
+            "version": "==6.2.1"
         },
         "sphinxcontrib-applehelp": {
             "hashes": [
@@ -3317,7 +3776,7 @@
                 "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b",
                 "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"
             ],
-            "markers": "python_version < '3.10'",
+            "markers": "python_version >= '3.7'",
             "version": "==3.15.0"
         }
     }
diff --git a/notebooks/README.md b/notebooks/README.md
index 4fff5bb..f22b805 100644
--- a/notebooks/README.md
+++ b/notebooks/README.md
@@ -4,3 +4,4 @@ The readme contains description of experiment notebooks in this repository.
 * [haystack-qa.ipynb](./haystack-qa.ipynb) explores the [Haystack framework](https://haystack.deepset.ai/) for question answering, both extractive and generative (with two different versions for that: a local seq2seq model and one based in the [OpenAI API](https://platform.openai.com/docs/introduction)).
 * [create-validation-dataset.ipynb](create-validation-dataset.ipynb): reads the FAQ questionnaire from the ROSA workshop documents and creates a fine-tuning or validation dataset for text generation models.
 * [langchain-openai.ipynb](langchain-openai.ipynb) explores the [langchain framework](https://langchain.readthedocs.io/en/latest/index.html) that helps develop with large language models for various tasks including [question answering](https://langchain.readthedocs.io/en/latest/modules/indexes/chain_examples/question_answering.html).
+* [gpu-footprint.ipynb](gpu-footprint.ipynb) computes gpu requirements of models with different number of model parameters.
diff --git a/notebooks/gpu-footprint.ipynb b/notebooks/gpu-footprint.ipynb
new file mode 100755
index 0000000..ca21f87
--- /dev/null
+++ b/notebooks/gpu-footprint.ipynb
@@ -0,0 +1,352 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## GPU Footprint\n",
+    "\n",
+    "This notebook computes gpu requirements of models with different number of model parameters. The results are shown in the outputs.\n",
+    "\n",
+    "Source: https://github.com/hwchase17/langchain/blob/master/langchain/llms/huggingface_pipeline.py"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "be76f7630cb8475eae71a1d99138ddcd",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "0it [00:00, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "from langchain.llms import HuggingFacePipeline\n",
+    "from transformers import AutoModelForCausalLM, AutoModelForSeq2SeqLM, AutoTokenizer, pipeline\n",
+    "import GPUtil\n",
+    "from numba import cuda\n",
+    "import gc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "| ID | Name     | Serial        | UUID                                     || GPU temp. | GPU util. | Memory util. || Memory total | Memory used | Memory free || Display mode | Display active |\n",
+      "-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
+      "|  0 | Tesla T4 | 1323921034295 | GPU-634f99e4-90c8-d992-a802-6d4246152a1c ||       22C |        0% |           0% ||      15360MB |         5MB |     14923MB || Enabled      | Disabled       |\n"
+     ]
+    }
+   ],
+   "source": [
+    "# View GPU utilization when nothing is running on it\n",
+    "device = -1  # cpu\n",
+    "if torch.cuda.is_available():\n",
+    "    torch.set_default_tensor_type(torch.cuda.FloatTensor)\n",
+    "    device = 0  # first GPU\n",
+    "# Get all available GPUs\n",
+    "gpus = GPUtil.getGPUs()\n",
+    "GPUtil.showUtilization(all=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "| ID | Name     | Serial        | UUID                                     || GPU temp. | GPU util. | Memory util. || Memory total | Memory used | Memory free || Display mode | Display active |\n",
+      "-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
+      "|  0 | Tesla T4 | 1323921034295 | GPU-634f99e4-90c8-d992-a802-6d4246152a1c ||       23C |        6% |           3% ||      15360MB |       481MB |     14447MB || Enabled      | Disabled       |\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Look at the GPU utilization when kernels are loaded\n",
+    "torch.ones((1, 1)).to(device)\n",
+    "GPUtil.showUtilization(all=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We see a memory of 481MB used just for loading kernels. Let's see what happens when the models are loaded. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Model selection\n",
+    "# A dictionary of models and their corresponding tasks\n",
+    "models = {\n",
+    "    \"bloom-1b7\": {\n",
+    "        \"task\": \"text-generation\",\n",
+    "        \"model\": \"bigscience/bloom-1b7\",\n",
+    "        \"extra_args\": {\"max_new_tokens\": 100},\n",
+    "    },\n",
+    "    \"bloomz-1b7\": {\n",
+    "        \"task\": \"text-generation\",\n",
+    "        \"model\": \"bigscience/bloomz-1b7\",\n",
+    "        \"extra_args\": {\"max_new_tokens\": 500, \"temperature\": 0.9},\n",
+    "    },\n",
+    "    \"gpt2\": {\n",
+    "        \"task\": \"text-generation\",\n",
+    "        \"model\": \"gpt2\",\n",
+    "        \"extra_args\": {\"max_new_tokens\": 30},\n",
+    "    },\n",
+    "    \"gpt2-large\": {\n",
+    "        \"task\": \"text-generation\",\n",
+    "        \"model\": \"gpt2-large\",\n",
+    "        \"extra_args\": {\"max_new_tokens\": 50},\n",
+    "    },\n",
+    "    \"mt0-large\": {\n",
+    "        \"task\": \"text2text-generation\",\n",
+    "        \"model\": \"bigscience/mt0-large\",\n",
+    "        \"extra_args\": {},\n",
+    "    },\n",
+    "    \"opt-1b3\": {\n",
+    "        \"task\": \"text-generation\",\n",
+    "        \"model\": \"facebook/opt-1.3b\",\n",
+    "        \"extra_args\": {\"max_new_tokens\": 100},\n",
+    "    },\n",
+    "    \"bloom-3b\": {\n",
+    "        \"task\": \"text-generation\",\n",
+    "        \"model\": \"bigscience/bloom-3b\",\n",
+    "        \"extra_args\": {\"max_new_tokens\": 100},\n",
+    "    },\n",
+    "    \"bloom-7b1\": {\n",
+    "        \"task\": \"text-generation\",\n",
+    "        \"model\": \"bigscience/bloom-7b1\",\n",
+    "        \"extra_args\": {\"max_new_tokens\": 100},\n",
+    "    },\n",
+    "    \"gpt-6b\":{\n",
+    "        \"task\": \"text-generation\",\n",
+    "        \"model\": \"EleutherAI/gpt-j-6B\",\n",
+    "        \"extra_args\": {\"max_new_tokens\": 100},\n",
+    "    }\n",
+    "}\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def load_model_on_gpu(model_id):\n",
+    "    \"\"\"\n",
+    "    The function loads the model (from its model_id) on the available GPU\n",
+    "    \"\"\"\n",
+    "    # A mapping between the task and the corresponding transformers class\n",
+    "    auto_classes = {\n",
+    "        \"text-generation\": AutoModelForCausalLM,\n",
+    "        \"text2text-generation\": AutoModelForSeq2SeqLM,\n",
+    "    }\n",
+    "\n",
+    "    task = models[model_id][\"task\"]\n",
+    "    model_name = models[model_id][\"model\"]\n",
+    "    auto_class = auto_classes[task]\n",
+    "    print(f\"Using a {task} pipeline with {model_name}\")\n",
+    "\n",
+    "    model = auto_class.from_pretrained(model_name).to(device)\n",
+    "\n",
+    "def show_utilization_models(model_ids):\n",
+    "    \"\"\"\n",
+    "    This function loads all the models from their model_ids, shows their gpu utilization and cleans up memory.\n",
+    "    \"\"\"\n",
+    "    for model_id in model_ids:\n",
+    "        load_model_on_gpu(model_id)\n",
+    "        GPUtil.showUtilization(all=True)\n",
+    "        torch.cuda.empty_cache()\n",
+    "        cuda.get_current_device().reset()\n",
+    "        gc.collect()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using a text-generation pipeline with bigscience/bloom-1b7\n",
+      "| ID | Name     | Serial        | UUID                                     || GPU temp. | GPU util. | Memory util. || Memory total | Memory used | Memory free || Display mode | Display active |\n",
+      "-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
+      "|  0 | Tesla T4 | 1320220104182 | GPU-e038c2e6-e540-d3ae-f932-68e51a562fd3 ||       33C |       20% |          59% ||      15360MB |      9011MB |      5917MB || Enabled      | Disabled       |\n",
+      "Using a text-generation pipeline with bigscience/bloomz-1b7\n",
+      "| ID | Name     | Serial        | UUID                                     || GPU temp. | GPU util. | Memory util. || Memory total | Memory used | Memory free || Display mode | Display active |\n",
+      "-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
+      "|  0 | Tesla T4 | 1320220104182 | GPU-e038c2e6-e540-d3ae-f932-68e51a562fd3 ||       32C |       11% |          59% ||      15360MB |      9011MB |      5917MB || Enabled      | Disabled       |\n",
+      "Using a text-generation pipeline with gpt2-large\n",
+      "| ID | Name     | Serial        | UUID                                     || GPU temp. | GPU util. | Memory util. || Memory total | Memory used | Memory free || Display mode | Display active |\n",
+      "-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
+      "|  0 | Tesla T4 | 1320220104182 | GPU-e038c2e6-e540-d3ae-f932-68e51a562fd3 ||       32C |       25% |          25% ||      15360MB |      3863MB |     11065MB || Enabled      | Disabled       |\n",
+      "Using a text-generation pipeline with facebook/opt-1.3b\n",
+      "| ID | Name     | Serial        | UUID                                     || GPU temp. | GPU util. | Memory util. || Memory total | Memory used | Memory free || Display mode | Display active |\n",
+      "-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
+      "|  0 | Tesla T4 | 1320220104182 | GPU-e038c2e6-e540-d3ae-f932-68e51a562fd3 ||       31C |        4% |          38% ||      15360MB |      5897MB |      9031MB || Enabled      | Disabled       |\n",
+      "Using a text2text-generation pipeline with bigscience/mt0-large\n",
+      "| ID | Name     | Serial        | UUID                                     || GPU temp. | GPU util. | Memory util. || Memory total | Memory used | Memory free || Display mode | Display active |\n",
+      "-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
+      "|  0 | Tesla T4 | 1320220104182 | GPU-e038c2e6-e540-d3ae-f932-68e51a562fd3 ||       32C |        5% |          35% ||      15360MB |      5317MB |      9611MB || Enabled      | Disabled       |\n"
+     ]
+    }
+   ],
+   "source": [
+    "model_ids_1 = [\"bloom-1b7\", \"bloomz-1b7\", \"gpt2-large\", \"opt-1b3\", \"mt0-large\"]\n",
+    "show_utilization_models(model_ids_1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using a text-generation pipeline with bigscience/bloom-3b\n",
+      "| ID | Name     | Serial        | UUID                                     || GPU temp. | GPU util. | Memory util. || Memory total | Memory used | Memory free || Display mode | Display active |\n",
+      "-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
+      "|  0 | Tesla T4 | 1320220104182 | GPU-e038c2e6-e540-d3ae-f932-68e51a562fd3 ||       35C |       17% |          94% ||      15360MB |     14443MB |       485MB || Enabled      | Disabled       |\n"
+     ]
+    }
+   ],
+   "source": [
+    "model_ids_2 = [\"bloom-3b\"]\n",
+    "show_utilization_models(model_ids_2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using a text-generation pipeline with EleutherAI/gpt-j-6B\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7a28c62da494433189cd35e3928ecabe",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading (…)lve/main/config.json:   0%|          | 0.00/930 [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f642a8222cf3463fa1780f74485ac67b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading pytorch_model.bin:   0%|          | 0.00/24.2G [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "model_ids_3 = [\"gpt-6b\", \"bloom-7b1\"]\n",
+    "show_utilization_models(model_ids_3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The 3B model takes around 94% of the GPU RAM and therefore 6B and 7B models can't be loaded into the GPU in fp32 precision."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Conclusion\n",
+    "This notebook loads models on the GPU and checks their GPU memory utilization. This cluster has Tesla T4 16GB GPUs out of which 15.36GB are available for use. The kernels take an additional 500MB. The results show memory taken up by different small models. The models that have no results were not able to run in the environment resources."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.9.14",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.14"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "dfef540ac477f3be91e5308acd671ac2a81f2c8cc1125947821b3502f71b441e"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}