[enhancement] support llama #575

void-main · 2023-04-24T07:39:00Z

Implement LlaMa as requested in issue #506 .

Steps to use

first convert llama-7b-hf weights from huggingface with huggingface_llama_convert.py: python3 huggingface_llama_convert.py -saved_dir=/path/to/export/folder/ -in_file=/path/to/llama-7b-hf -infer_gpu_num=1 -weight_data_type=fp16 -model_name=llama_7b

next, compile and run llama_example.

Test case

start_ids.csv: [0, 18637, 29892, 526, 366, 1136, 455, 2470, 29973, 1815, 366, 5193, 304, 592, 29973]
out: [0,18637,29892,526,366,1136,455,2470,29973,1815,366,5193,304,592,29973,18637,29892,526,366,1136,455,2470,29973,1815,366,5193,304,592,29973,18637,29892,526,366,1136,455,2470,29973,1815,366,5193,304,592,29973,18637,29892,526,366]

src/fastertransformer/models/llama/Llama.cc

syslot · 2023-04-25T16:36:30Z

This implement for llama is very meaningful and do you test the performance of this ? How fast can this be when compares with vanilla transformers api?

src/fastertransformer/triton_backend/llama/LlamaTritonModel.cc

void-main · 2023-04-27T01:31:07Z

This implement for llama is very meaningful and do you test the performance of this ? How fast can this be when compares with vanilla transformers api?

I've been super busy lately, don't quite have the time for performance comparison, hopefully someone will do the favor and compare FT with transformers api. :-)

152334H · 2023-04-28T07:26:33Z

Does this implement int8 (or even 4bit) by any chance?

src/fastertransformer/triton_backend/llama/LlamaTritonModelInstance.h

…tance.h Co-authored-by: Bram Wasti <[email protected]>

void-main · 2023-04-30T00:31:07Z

Some updates:

supported bf16
supported triton decouple mode
verified that Llama 65B is working

…into main

pineking · 2023-05-01T03:29:56Z

Implement LlaMa as requested in issue #506 .

Steps to use

first convert llama-7b-hf weights from huggingface with huggingface_llama_convert.py: python3 huggingface_llama_convert.py -saved_dir=/path/to/export/folder/ -in_file=/path/to/llama-7b-hf -infer_gpu_num=1 -weight_data_type=fp16 -model_name=llama_7b

next, compile and run llama_example.

Test case

start_ids.csv: [0, 18637, 29892, 526, 366, 1136, 455, 2470, 29973, 1815, 366, 5193, 304, 592, 29973] out: [0,18637,29892,526,366,1136,455,2470,29973,1815,366,5193,304,592,29973,18637,29892,526,366,1136,455,2470,29973,1815,366,5193,304,592,29973,18637,29892,526,366,1136,455,2470,29973,1815,366,5193,304,592,29973,18637,29892,526,366]

what's the parameters for kernel-autotuning for llama model?

atyshka · 2023-05-01T13:42:53Z

Does this implement int8 (or even 4bit) by any chance?

FasterTransformer doesn't seem to support int4 at all right now. I would be interested in helping with int8 though, that should enable the 65B model to run tensor-parallel on my 2x A6000 GPUs.

happytree09 · 2023-05-01T19:25:51Z

Does this implement int8 (or even 4bit) by any chance?

FasterTransformer doesn't seem to support int4 at all right now. I would be interested in helping with int8 though, that should enable the 65B model to run tensor-parallel on my 2x A6000 GPUs.

+1 happy to contribute to this

src/fastertransformer/models/llama/Llama.h

lucasjinreal · 2023-05-25T08:56:56Z

@void-main Have compared with ggml's llama.cpp with cuBlas support?

dengzheng-cloud · 2023-06-02T03:39:00Z

examples/cpp/llama/llama_config.ini

+num_layer = 32
+rotary_embedding = 128
+vocab_size = 32000
+start_id = 0


add layernorm_eps=1e-06 will help new beginers.

handoku · 2023-06-09T11:18:01Z

Hi. I've recently tested this implementation on blip2_vicuna_instruct. It utilizes vit_qformer's embedding as a prefix_soft_embedding, which will be fed into vicuna with prompt's token_ids.

According to my test result, I found that:
When testing only vicuna-13b, FT outputs same quality text as huggingface's.
However, when token_ids are fed along with prefix_soft_embedding, a noticeable quality decrease occurs.

For example,
image:

prompt: Describe the environment in which the product in the middle of the image is located

pytorch output：

. The product in the middle of this image is located within a refrigerator, surrounded by various fruits and vegetables on both sides as well

FT output:

. The refrigerator is open and filled with food.
The refrigerator is open and filled with food.

Does anyone has experience in using fasterTransformer's prefix soft prompt feature. What problem might cause this issue. Counld it be a usage mistake? I need some hits to debug it.

Thanks in advance!

[EDITED]: issue solved

sleepwalker2017 · 2023-06-19T09:09:49Z

@void-main Hi, I'm also in Beijing and I'm a developer in AI inference. could I have your wechat?

void-main · 2023-06-20T04:18:57Z

@void-main Hi, I'm also in Beijing and I'm a developer in AI inference. could I have your wechat?

sure, try send me an email. :-)

frankxyy · 2023-06-27T02:32:02Z

I found that the results of rotary embedding is different for FT and huggingface. Has anyone met similar problems?

UnknownSwordsman · 2023-06-28T07:14:05Z

@void-main Hello，i found a bug that after multiple (thousands of) batch（20） inference, some batches may output randomly. But if the triton service is restarted, it can be inferred normally.

When the batch size is equal 5, I haven't found it yet.

Prompt Mixed Chinese and English
Some Answer Example:

该��ate-to-p>\n\n\n\n\n\n\n\n\n\n\n\n\nIt's a\n\nIt's a new-est\nIt in the\nIt's at all about\nIt's at the\nIt's at the\nIt's at the\nIt's\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's 

该宏在况况冲况��'s 不, 不, 它的 它的 ��, ��\n\n\n\n\n\n\n\n\n\n\n\nJupit was not you be ��, ��\n/b\n/and ��\n/��\n/��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/��\n/\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��

Compile based on Fastertransformer Backend

Device: V100/ A100 4gpu
Model: Vicuna 13B-v1.1
parameters: top_k = 1, output_token_len = 500, batch_size = 20

UnknownSwordsman · 2023-06-28T07:22:11Z

Another problem is When batch inference is used, the results generated by the same prompt are different.

paramters: top_k=1, random_seed=1, output_len=500
device: T4/ A100 4-gpu by triton sever

prompt = "写一篇关于爱情的故事"

answer:

['text': '。\n\n爱情，这个词汇，它既是最美妙的东西，又是最艰难的。它可以让人感到无比的高昂，也可以让人陷入无比的低谷。\n\n有一天，有两个人，他们分别是艾尔和卡洛斯。艾尔和卡洛斯是在一个酒店里相遇的。他们在一起，聊天，发现彼此都有着相似的经历。他们都是单身，都在寻找真爱。\n\n他们决定一起去旅行，去探索这个世界。他们在旅途中，发现彼此之间的感情越来越深。他们一起经历了许多困难和挑战，但是他们始终相互扶持，相互支持。\n\n最终，他们到达了一个美丽的小镇，这里是他们想要的地方。他们决定在这里生活，共同度过剩下的生活。他们彼此扶持，一起面对未来，一起迎接挑战。\n\n他们的爱情，不是一种刻意的选择，而是一种自然的选择。他们在彼此的陪伴下，找到了真正的意义。他们的爱情，是一种强大的力量，可以在任何情况下帮助他们克服困难。\n',
   'index': 0},
  {'text': '。\n\n爱情，这个词汇，它既是最美妙的东西，又是最艰难的。它可以让人感到无比的高昂，也可以让人陷入无比的低谷。\n\n有一天，有两个人，他们分别是艾尔和卡洛斯。艾尔和卡洛斯是在一个酒店里相遇的。他们在一起，聊天，发现彼此都有着相似的经历。他们都是单身，都在寻找真爱。\n\n他们决定一起去旅行，去探索这个世界。他们在旅途中，发现彼此之间的感情越来越深。他们一起经历了许多困难和挑战，但是他们始终相互扶持，相互支持。\n\n最终，他们到达了一个美丽的小镇，这里是他们想要的地方。他们决定在这里生活，共同度过剩下的生活。他们彼此扶持，一起面对未来，一起迎接挑战。\n\n他们的爱情，不是一种刻意的选择，而是一种自然的选择。他们在彼此的陪伴下，找到了真正的意义。他们的爱情，是一种强大的力量，可以在任何情况下帮助他们克服困难。\n',
   'index': 1},
  {'text': '。\n\n爱情，这个词汇，它既是最美妙的东西，又是最艰难的。它可以让人感到无比的高昂，也可以让人陷入无比的低谷。\n\n有一天，有两个人，他们分别是艾尔和卡洛斯。艾尔和卡洛斯是在一个酒店里相遇的。他们在一起，聊天，发现彼此都有着相似的经历。他们都是单身，都在寻找真爱。\n\n他们决定一起去旅行，去探索这个世界。他们在旅途中，发现彼此之间的感情越来越深。他们一起经历了许多困难和挑战，但是他们始终相互扶持，相互支持。\n\n最终，他们到达了一个美丽的小镇，这里是他们想要的地方。他们决定在这里生活，共同度过剩下的生活。他们彼此扶持，一起面对未来，一起迎接挑战。\n\n他们的爱情，不是一种刻意的选择，而是一种自然的选择。他们在彼此的陪伴下，找到了真正的意义。他们的爱情，是一种强大的力量，可以战胜一切困难。\n\n这是一个关于�',
   'index': 2},
  {'text': '。\n\n爱情，这个词汇，它既是最美妙的东西，又是最艰难的。它可以让人感到无比的高昂，也可以让人陷入无比的低谷。\n\n有一天，有两个人，他们分别是艾尔和卡洛斯。艾尔和卡洛斯是在一个酒店里相遇的。他们在一起，聊天，发现彼此都有着相似的经历。他们都是单身，都在寻找真爱。\n\n他们决定一起去旅行，去探索这个世界。他们在旅途中，发现彼此之间的感情越来越深。他们一起经历了许多困难和挑战，但是他们始终相互扶持，相互支持。\n\n最终，他们到达了一个美丽的小镇，这里是他们想要的地方。他们决定在这里生活，共同度过剩下的生活。他们彼此扶持，一起面对未来，一起迎接挑战。\n\n他们的爱情，不是一种刻意的选择，而是一种自然的选择。他们在彼此的陪伴下，找到了真正的意义。他们的爱情，是一种强大的力量，可以在任何情况下帮助他们克服困难。\n',
   'index': 3},
  {'text': '。\n\n爱情，这个词汇，它既是最美妙的东西，又是最艰难的。它可以让人感到无比的高昂，也可以让人陷入无比的低谷。\n\n有一天，有两个人，他们分别是艾尔和卡洛斯。艾尔和卡洛斯是在一个酒店里相遇的。他们在一起，聊天，发现彼此都有着相似的经历。他们都是单身，都在寻找真爱。\n\n他们决定一起去旅行，去探索这个世界。他们在旅途中，发现彼此之间的感情越来越深。他们一起经历了许多困难和挑战，但是他们始终相互扶持，相互支持。\n\n最终，他们到达了一个美丽的小镇，这里是他们想要的地方。他们决定在这里生活，共同度过剩下的生活。他们彼此扶持，一起面对未来，一起迎接挑战。\n\n他们的爱情，不是一种刻意的选择，而是一种自然的选择。他们在彼此的陪伴下，找到了真正的意义。他们的爱情，是一种强大的力量，可以战胜一切困难。\n\n这是一个关于�', 'index': 4}]

prnake · 2023-06-28T09:12:34Z

src/fastertransformer/models/llama/Llama.h

+    size_t rotary_embedding_dim_;
+    float layernorm_eps_;
+
+    static constexpr bool  neox_rotary_style_ = true;


This should be false.

@prnake I test it and only true output normal value

prnake · 2023-06-28T09:14:51Z

It seems that torch.cos() and c cos func generates slightly different results which leads to the different results of rotary embedding. Anyone has idea for the solution?

You are right, the model should use the basic type of rotary.

CN-COTER · 2023-06-29T12:25:24Z

First of all, thx for your Implement of ft LlaMa.@void-main I push a PR to support Int8 and share context. Anyone can help me to check it?

void-main · 2023-06-30T02:04:51Z

Hi @CN-COTER , thanks for the contribution! really appreciate it!
I've checked your code and started a review, could you please take a look. 🎉

support int8 & share context

upload code: llama int8&share_context triton backend

fix bug: ft-llama-int8 output is incorrect

fix llama

double-vin · 2023-07-25T09:20:57Z

Implement LlaMa as requested in issue #506 .

Steps to use

first convert llama-7b-hf weights from huggingface with huggingface_llama_convert.py: python3 huggingface_llama_convert.py -saved_dir=/path/to/export/folder/ -in_file=/path/to/llama-7b-hf -infer_gpu_num=1 -weight_data_type=fp16 -model_name=llama_7b

next, compile and run llama_example.

Test case

start_ids.csv: [0, 18637, 29892, 526, 366, 1136, 455, 2470, 29973, 1815, 366, 5193, 304, 592, 29973] out: [0,18637,29892,526,366,1136,455,2470,29973,1815,366,5193,304,592,29973,18637,29892,526,366,1136,455,2470,29973,1815,366,5193,304,592,29973,18637,29892,526,366,1136,455,2470,29973,1815,366,5193,304,592,29973,18637,29892,526,366]

My start_ids.csv: [0, 18637, 29892, 526, 366, 1136, 455, 2470, 29973, 1815, 366, 5193, 304, 592, 29973]
out:
0 18637 29892 526 366 1136 455 2470 29973 1815 366 5193 304 592 29973 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 2 2991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991

decode out:
Hey, are you consciours? Can you talk to me?olgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolg

It looks like there's a problem with the out and decode out. Please give me some suggestions.

KeKe-Deng · 2023-07-25T09:21:17Z

Email has been received.This is an automatic reply, confirming that your email was received.Thank you.

realgump · 2023-08-01T02:48:10Z

@void-main Hello，i found a bug that after multiple (thousands of) batch（20） inference, some batches may output randomly. But if the triton service is restarted, it can be inferred normally.

When the batch size is equal 5, I haven't found it yet.

Prompt Mixed Chinese and English Some Answer Example:

该��ate-to-p>\n\n\n\n\n\n\n\n\n\n\n\n\nIt's a\n\nIt's a new-est\nIt in the\nIt's at all about\nIt's at the\nIt's at the\nIt's at the\nIt's\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's the\nIt's 

该宏在况况冲况��'s 不, 不, 它的 它的 ��, ��\n\n\n\n\n\n\n\n\n\n\n\nJupit was not you be ��, ��\n/b\n/and ��\n/��\n/��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/\n/ ��\n/��\n/\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��\n/��

Compile based on Fastertransformer Backend

Device: V100/ A100 4gpu Model: Vicuna 13B-v1.1 parameters: top_k = 1, output_token_len = 500, batch_size = 20

Same issue. Have you find the solution?

double-vin · 2023-08-02T01:16:08Z

Implement LlaMa as requested in issue #506 .

Steps to use

first convert llama-7b-hf weights from huggingface with huggingface_llama_convert.py: python3 huggingface_llama_convert.py -saved_dir=/path/to/export/folder/ -in_file=/path/to/llama-7b-hf -infer_gpu_num=1 -weight_data_type=fp16 -model_name=llama_7b
next, compile and run llama_example.

Test case

start_ids.csv: [0, 18637, 29892, 526, 366, 1136, 455, 2470, 29973, 1815, 366, 5193, 304, 592, 29973] out: [0,18637,29892,526,366,1136,455,2470,29973,1815,366,5193,304,592,29973,18637,29892,526,366,1136,455,2470,29973,1815,366,5193,304,592,29973,18637,29892,526,366,1136,455,2470,29973,1815,366,5193,304,592,29973,18637,29892,526,366]

My start_ids.csv: [0, 18637, 29892, 526, 366, 1136, 455, 2470, 29973, 1815, 366, 5193, 304, 592, 29973] out: 0 18637 29892 526 366 1136 455 2470 29973 1815 366 5193 304 592 29973 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 2 2991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991 22991

decode out: Hey, are you consciours? Can you talk to me?olgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolgolg

It looks like there's a problem with the out and decode out. Please give me some suggestions.

@void-main Please give some suggestions. Thank you！

jcao-ai · 2023-08-08T02:19:42Z

Will llama-2 70b arch be supported in the future? @void-main Thanks

void-main added 2 commits April 23, 2023 12:12

get llama coded

f3bd8e6

make the code work :yay:

a32fc1d

cameronfr reviewed Apr 24, 2023

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src/fastertransformer/models/llama/Llama.cc Show resolved Hide resolved

void-main added 7 commits April 24, 2023 09:30

fix llama rms ln

ce8700f

add bf16 support

91989cb

add triton model for streaming callback

4bc97c3

register RMS for bf16

a6d51ec

revert bf16

7a72ca3

revert bf16

9820565

bugfix

bfeebef

yinghai reviewed Apr 26, 2023

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src/fastertransformer/triton_backend/llama/LlamaTritonModel.cc Outdated Show resolved Hide resolved

arnocandel mentioned this pull request Apr 27, 2023

NVIDIA Triton inference support h2oai/h2ogpt#87

Open

7 tasks

add megatron llama convert

0379cc5

void-main force-pushed the main branch from 1b0eb79 to 0379cc5 Compare April 28, 2023 07:31

bwasti reviewed Apr 28, 2023

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src/fastertransformer/triton_backend/llama/LlamaTritonModelInstance.h Outdated Show resolved Hide resolved

void-main and others added 4 commits April 29, 2023 01:15

Update src/fastertransformer/triton_backend/llama/LlamaTritonModelIns…

d65adf1

…tance.h Co-authored-by: Bram Wasti <[email protected]>

donot callback too frequnetly

cf1b9b1

add bf16

95afed4

make sure examples work for bf16

9aee02e

void-main added 2 commits April 30, 2023 02:54

support bf16 conversion with bfloat 16 numpy ext

8ddac81

Merge branch 'main' of https://github.com/void-main/FasterTransformer …

694faec

…into main

bugfix

40fbe48

michaelroyzen reviewed May 1, 2023

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src/fastertransformer/models/llama/Llama.h Outdated Show resolved Hide resolved

dengzheng-cloud reviewed Jun 2, 2023

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handoku mentioned this pull request Jun 9, 2023

[soft prompt] llama generation quality decrease when using soft prompt #661

Closed

fix name

50fdb0c

prnake reviewed Jun 28, 2023

View reviewed changes

support int8 & share context

3c03564

shaoxin and others added 10 commits June 30, 2023 14:08

update code with comments from reviewer

6f0469f

rm unused code

0e6ae5b

Merge pull request #1 from CN-COTER/dev_support_int8_share_ctx

98435f1

support int8 & share context

upload code: llama int8&share_context triton backend

9e374ef

Merge pull request #2 from CN-COTER/dev_support_int8_share_ctx

69de159

upload code: llama int8&share_context triton backend

fix bug: ft-llama-int8 output is incorrect

c137bb5

Merge pull request #3 from CN-COTER/dev_support_int8_share_ctx

3469ff0

fix bug: ft-llama-int8 output is incorrect

fix llama

99a844c

remove padded_embedding_bias_

f1dd8fb

Merge pull request #4 from yandai/llama

e770ddf

fix llama

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[enhancement] support llama #575

[enhancement] support llama #575

void-main commented Apr 24, 2023

syslot commented Apr 25, 2023

void-main commented Apr 27, 2023

152334H commented Apr 28, 2023

void-main commented Apr 30, 2023

pineking commented May 1, 2023

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atyshka commented May 1, 2023

happytree09 commented May 1, 2023

lucasjinreal commented May 25, 2023

dengzheng-cloud Jun 2, 2023

handoku commented Jun 9, 2023 •

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sleepwalker2017 commented Jun 19, 2023

void-main commented Jun 20, 2023

frankxyy commented Jun 27, 2023

UnknownSwordsman commented Jun 28, 2023 •

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UnknownSwordsman commented Jun 28, 2023

prnake Jun 28, 2023

jcao-ai Jun 30, 2023

prnake commented Jun 28, 2023

CN-COTER commented Jun 29, 2023

void-main commented Jun 30, 2023

double-vin commented Jul 25, 2023

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KeKe-Deng commented Jul 25, 2023 via email

realgump commented Aug 1, 2023

double-vin commented Aug 2, 2023

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jcao-ai commented Aug 8, 2023

[enhancement] support llama #575

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[enhancement] support llama #575

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void-main commented Apr 24, 2023

Steps to use

Test case

syslot commented Apr 25, 2023

void-main commented Apr 27, 2023

152334H commented Apr 28, 2023

void-main commented Apr 30, 2023

pineking commented May 1, 2023

Steps to use

Test case

atyshka commented May 1, 2023

happytree09 commented May 1, 2023

lucasjinreal commented May 25, 2023

dengzheng-cloud Jun 2, 2023

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handoku commented Jun 9, 2023 • edited Loading

sleepwalker2017 commented Jun 19, 2023

void-main commented Jun 20, 2023

frankxyy commented Jun 27, 2023

UnknownSwordsman commented Jun 28, 2023 • edited Loading

UnknownSwordsman commented Jun 28, 2023

prnake Jun 28, 2023

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jcao-ai Jun 30, 2023

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prnake commented Jun 28, 2023

CN-COTER commented Jun 29, 2023

void-main commented Jun 30, 2023

double-vin commented Jul 25, 2023

Steps to use

Test case

KeKe-Deng commented Jul 25, 2023 via email

realgump commented Aug 1, 2023

double-vin commented Aug 2, 2023

Steps to use

Test case

jcao-ai commented Aug 8, 2023

handoku commented Jun 9, 2023 •

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UnknownSwordsman commented Jun 28, 2023 •

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