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Model: abhishek-ch/biomistral-7b-synthetic-ehr Source: Original Platform
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README.md
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---
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language:
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- en
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- fr
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- nl
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- es
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- it
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- pl
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- ro
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- de
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license: apache-2.0
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library_name: transformers
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tags:
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- mergekit
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- merge
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- dare
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- medical
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- biology
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- mlx
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datasets:
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- health_fact
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base_model:
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- BioMistral/BioMistral-7B
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- mistralai/Mistral-7B-Instruct-v0.1
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pipeline_tag: text-generation
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---
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# abhishek-ch/biomistral-7b-synthetic-ehr
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This model was converted to MLX format from [`BioMistral/BioMistral-7B-DARE`]().
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Refer to the [original model card](https://huggingface.co/BioMistral/BioMistral-7B-DARE) for more details on the model.
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## Use with mlx
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```bash
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pip install mlx-lm
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```
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The model was LoRA fine-tuned on [health_facts](https://huggingface.co/datasets/health_fact) and
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Synthetic EHR dataset inspired by MIMIC-IV using the format below, for 1000 steps (~1M tokens) using mlx.
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```python
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def format_prompt(prompt:str, question: str) -> str:
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return """<s>[INST]
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## Instructions
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{}
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## User Question
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{}.
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[/INST]</s>
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""".format(prompt, question)
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```
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Example For Synthetic EHR Diagnosis System Prompt
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```
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You are an expert in provide diagnosis summary based on clinical notes inspired by MIMIC-IV-Note dataset.
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These notes encompass Chief Complaint along with Patient Summary & medical admission details.
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```
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Example for Healthfacts Check System Prompt
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```
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You are a Public Health AI Assistant. You can do the fact-checking of public health claims. \nEach answer labelled with true, false, unproven or mixture. \nPlease provide the reason behind the answer
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```
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## Loading the model using `mlx`
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```python
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from mlx_lm import generate, load
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model, tokenizer = load("abhishek-ch/biomistral-7b-synthetic-ehr")
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response = generate(
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fused_model,
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fused_tokenizer,
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prompt=format_prompt(prompt, question),
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verbose=True, # Set to True to see the prompt and response
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temp=0.0,
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max_tokens=512,
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)
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```
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## Loading the model using `transformers`
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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repo_id = "abhishek-ch/biomistral-7b-synthetic-ehr"
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tokenizer = AutoTokenizer.from_pretrained(repo_id)
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model = AutoModelForCausalLM.from_pretrained(repo_id)
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model.to("mps")
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input_text = format_prompt(system_prompt, question)
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input_ids = tokenizer(input_text, return_tensors="pt").to("mps")
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outputs = model.generate(
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**input_ids,
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max_new_tokens=512,
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)
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print(tokenizer.decode(outputs[0]))
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```
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config.json
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"num_hidden_layers": 32,
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"hidden_act": "silu",
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|
||||
"model.layers.9.mlp.down_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.mlp.gate_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.mlp.up_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00003.safetensors",
|
||||
"model.norm.weight": "model-00003-of-00003.safetensors"
|
||||
}
|
||||
}
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
91122
tokenizer.json
Normal file
91122
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
43
tokenizer_config.json
Normal file
43
tokenizer_config.json
Normal file
@@ -0,0 +1,43 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [],
|
||||
"bos_token": "<s>",
|
||||
"chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token + ' ' }}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"legacy": true,
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": null,
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user