diff --git a/.gitignore b/.gitignore
index 922c797..b164ad0 100644
--- a/.gitignore
+++ b/.gitignore
@@ -3,3 +3,6 @@ __pycache__
 .venv
 
 meta
+
+# using prettier for formatting the markdown
+.prettierrc
diff --git a/README.md b/README.md
index 5e83b5f..b073fc6 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,7 @@
 # LoRA inspector
 
 <!--toc:start-->
+
 - [LoRA inspector](#lora-inspector)
   - [Install](#install)
   - [Usage](#usage)
@@ -9,12 +10,19 @@
   - [Development](#development)
   - [Future](#future)
   - [Reference](#reference)
-<!--toc:end-->
+  <!--toc:end-->
 
-Inspect LoRA files for meta info (and hopefully quantitative analysis of the LoRA weights)
+Inspect LoRA files for meta info (and hopefully quantitative analysis of the
+LoRA weights)
 
 - view training parameters
-- extract metadata to be stored (we can store it in json currently)
+- extract metadata to be stored (we can store it in JSON currently)
+
+---
+
+_NOTE_ this is a work in progress and not meant for production use. _NOTE_
+ 
+---
 
 ## Install
 
@@ -27,7 +35,11 @@ torch
 safetensors
 ```
 
-Can install them using `pip install torch safetensors`, make a venv/conda with them, or add this script to your training directory (to access the dependencies).
+Can install them one of the following:
+
+- `pip install torch safetensors`,
+- make/use with a venv/conda
+- add this script to your training directory (to access the dependencies).
 
 ## Usage
 
@@ -116,7 +128,9 @@ network dim/rank: 8.0 alpha: 4.0 module: networks.lora
 
 ### Save meta
 
-We also have support for saving the meta that is extracted and converted from strings. We can then save those to a JSON file. These will save the metadata into `meta/alorafile.safetensors-{session_id}.json` in the meta directory. 
+We also have support for saving the meta that is extracted and converted from
+strings. We can then save those to a JSON file. These will save the metadata
+into `meta/alorafile.safetensors-{session_id}.json` in the meta directory.
 
 ```bash
 $ python lora-inspector.py ~/loras/alorafile.safetensors --save_meta
@@ -135,7 +149,7 @@ network dim/rank: 8.0 alpha: 4.0 module: networks.lora
 
 ## Development
 
-Formatted using [`black`](https://github.com/psf/black). 
+Formatted using [`black`](https://github.com/psf/black).
 
 ## Future
 
diff --git a/parsers.py b/parsers.py
deleted file mode 100644
index 75e2bf1..0000000
--- a/parsers.py
+++ /dev/null
@@ -1,118 +0,0 @@
-import json
-from datetime import datetime
-from typing import Callable
-
-
-def to_datetime(str: str):
-    return datetime.fromtimestamp(float(str))
-
-
-parsers: dict[str, Callable] = {
-    "int": int,
-    "float": float,
-    "json": json.loads,
-    "bool": bool,
-    "dt": to_datetime,
-    "str": str,
-}
-
-
-schema: dict[str, str] = {
-    "ss_learning_rate": "float",
-    "ss_max_bucket_reso": "int",
-    "ss_text_encoder_lr": "float",
-    "ss_epoch": "int",
-    "ss_unet_lr": "float",
-    "ss_seed": "int",
-    "ss_max_train_steps": "int",
-    "ss_sd_model_name": "str",
-    "ss_new_vae_hash": "str",
-    "ss_resolution": "str",
-    "ss_full_fp16": "bool",
-    "ss_vae_hash": "str",
-    "ss_gradient_checkpoint": "bool",
-    "ss_output_name": "bool",
-    "ss_bucket_info": "json",
-    "sshs_model_hash": "str",
-    "sshs_legacy_hash": "str",
-    "ss_caption_dropout_rate": "float",
-    "ss_caption_dropout_every_n_epochs": "int",
-    "ss_caption_tag_dropout_rate": "float",
-    "ss_sd_scripts_commit_hash": "str",
-    "ss_gradient_checkpointing": "bool",
-    "ss_training_finished_at": "dt",
-    "ss_vae_name": "str",
-    "ss_total_batch_size": "int",
-    "ss_batch_size_per_device": "int",
-    "ss_color_aug": "bool",
-    "ss_flip_aug": "bool",
-    "ss_lr_warmup_steps": "int",
-    "ss_network_module": "str",
-    "ss_lr_scheduler": "str",
-    "ss_num_epochs": "int",
-    "ss_mixed_precision": "str",
-    "ss_shuffle_caption": "bool",
-    "ss_training_started_at": "dt",
-    "ss_v2": "bool",
-    "ss_keep_tokens": "bool",
-    "ss_random_crop": "bool",
-    "ss_cache_latents": "bool",
-    "ss_gradient_accumulation_steps": "int",
-    "ss_clip_skip": "int",
-    "ss_dataset_dirs": "json",
-    "ss_training_comment": "str",
-    "ss_network_alpha": "float",
-    "ss_network_dim": "float",
-    "ss_reg_dataset_dirs": "json",
-    "ss_num_batches_per_epoch": "int",
-    "ss_num_reg_images": "int",
-    "ss_max_token_length": "int",
-    "ss_sd_new_model_hash": "int",
-    "ss_face_crop_aug_range": "str",
-    "ss_min_bucket_reso": "int",
-    "ss_bucket_no_upscale": "bool",
-    "ss_prior_loss_weight": "float",
-    "ss_network_args": "json",
-    "ss_enable_bucket": "bool",
-    "ss_num_train_images": "int",
-    "ss_lowram": "bool",
-    "ss_optimizer": "str",
-    "ss_tag_frequency": "json",
-    "ss_session_id": "str",
-    "ss_max_grad_norm": "float",
-    "ss_noise_offset": "float",
-}
-
-
-def parse_item(key: str, value: str) -> int | float | bool | datetime | str | None:
-    if key not in schema:
-        print(f"invalid key in schema {key}")
-        return value
-
-    if schema[key] == "int" and value == "None":
-        return None
-
-    if schema[key] == "float" and value == "None":
-        return None
-
-    print(key)
-    return parsers[schema[key]](value)
-
-
-def parse(entries: dict[str, str]):
-    results = {}
-    for k in entries.keys():
-        v = entries[k]
-        results[k] = parse_item(k, v)
-    return results
-
-
-# if __name__ == "__main__":
-#     with open("meta/last.safetensors.json") as f:
-#         loaded: dict[str, str] = json.load(f)
-#         results = {}
-#         for (k, v) in parse(loaded):
-#             # v = loaded[k]
-#             results[k] = v
-#
-#         print(json.dumps(results, default=str))