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Model: hongzhouyu/FineMedLM-o1
Source: Original Platform
---
 .gitattributes                                |    5 +
 README.md                                     |  107 +
 config.json                                   |   35 +
 generation_config.json                        |    9 +
 model-00001-of-00004.safetensors              |    3 +
 model-00002-of-00004.safetensors              |    3 +
 model-00003-of-00004.safetensors              |    3 +
 model-00004-of-00004.safetensors              |    3 +
 model.safetensors.index.json                  |  298 +++
 ...941.dpo0--958cfdb21e51-doqv5oixhk.556397.0 |  Bin 0 -> 23847 bytes
 special_tokens_map.json                       |   23 +
 tokenizer.json                                |    3 +
 tokenizer_config.json                         | 2064 +++++++++++++++++
 trainer_state.json                            |  409 ++++
 training_args.bin                             |  Bin 0 -> 7800 bytes
 15 files changed, 2965 insertions(+)
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 create mode 100644 special_tokens_map.json
 create mode 100644 tokenizer.json
 create mode 100644 tokenizer_config.json
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 create mode 100644 training_args.bin

diff --git a/.gitattributes b/.gitattributes
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index 0000000..51a5b10
--- /dev/null
+++ b/.gitattributes
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+model-00001-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text
+model-00002-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text
+model-00003-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text
+model-00004-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text
diff --git a/README.md b/README.md
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--- /dev/null
+++ b/README.md
@@ -0,0 +1,107 @@
+---
+license: mit
+datasets:
+- hongzhouyu/FineMed-SFT
+- hongzhouyu/FineMed-DPO
+language:
+- en
+- zh
+base_model:
+- meta-llama/Llama-3.1-8B
+- hongzhouyu/FineMedLM
+library_name: transformers
+tags:
+- medical
+---
+
+<div align="center">
+<h1>
+  FineMedLM-o1
+</h1>
+</div>
+
+<div align="center">
+<a href="https://github.com/hongzhouyu/FineMed" target="_blank">GitHub</a> | <a href="https://arxiv.org/abs/2501.09213" target="_blank">Paper</a>
+</div>
+
+# <span>Introduction</span>
+**FineMedLM-o1** is a specialized medical LLM engineered for advanced medical reasoning. It employs a multi-step reasoning process, iteratively reflecting on and refining its thought process before delivering a final response.
+
+For more information, visit our GitHub repository.
+
+# <span>Usage</span>
+You can use FineMedLM-o1 in the same way as `Llama-3.1-8B-Instruct`:
+
+(⚠️**Note**: Please use the system prompt we provide to achieve better inference results.)
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+main_model_name = "yuhongzhou/FineMedLM"  
+model = AutoModelForCausalLM.from_pretrained(main_model_name, device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained(main_model_name)
+
+prompt = (
+    """The following are multiple choice questions (with answers) about health. Think step by step and then finish your answer with "the answer is (X)" where X is the correct letter choice.
+
+
+Question:
+Polio can be eradicated by which of the following?
+Options:
+A. Herbal remedies
+B. Use of antibiotics
+C. Regular intake of vitamins
+D. Administration of tetanus vaccine
+E. Attention to sewage control and hygiene
+F. Natural immunity acquired through exposure
+G. Use of antiviral drugs
+Answer: Let's think step by step.
+"""
+)
+
+messages = [
+    {"role": "system", "content": """You are a helpful professional doctor. You need to generate an answer based on the given problem and thoroughly explore the problem through a systematic and long-term thinking process to provide a final and accurate solution. This requires a comprehensive cycle of analysis, summary, exploration, re-evaluation, reflection, backtracking and iteration to form a thoughtful thinking process. Use the background information provided in the text to assist in formulating the answer. Follow these answer guidelines:
+1. Please structure your response into two main sections: **Thought** and **Summarization**.
+2. During the **Thought** phase, think step by step based on the given text content. If the text content is used, it must be expressed.
+3. During the **Summarization** phase, based on the thinking process in the thinking phase, give the final answer to the question.
+Here is the question: """},
+    {"role": "user", "content": prompt}
+]
+
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+print(text)
+
+model_inputs = tokenizer(text, return_tensors="pt").to(model.device)
+
+print("-----start generate-----")
+generated_ids = model.generate(
+    model_inputs.input_ids,
+    max_new_tokens=2048,
+    eos_token_id=tokenizer.eos_token_id
+)
+
+answer = tokenizer.decode(generated_ids[0], skip_special_tokens=False)
+print(answer)
+```
+
+FineMedLM-o1 adopts a *slow-thinking* approach, with outputs formatted as:
+
+```
+**Thought**
+[Reasoning process]
+
+**Summarization**
+[Output]
+```
+
+# <span>Citation</span>
+```
+@misc{yu2025finemedlmo1enhancingmedicalreasoning,
+    title={FineMedLM-o1: Enhancing the Medical Reasoning Ability of LLM from Supervised Fine-Tuning to Test-Time Training}, 
+    author={Hongzhou Yu and Tianhao Cheng and Ying Cheng and Rui Feng},
+    year={2025},
+    eprint={2501.09213},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL},
+    url={https://arxiv.org/abs/2501.09213}, 
+}
+```
\ No newline at end of file
diff --git a/config.json b/config.json
new file mode 100644
index 0000000..a153282
--- /dev/null
+++ b/config.json
@@ -0,0 +1,35 @@
+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 8.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.50.0",
+  "use_cache": true,
+  "vocab_size": 128256
+}
diff --git a/generation_config.json b/generation_config.json
new file mode 100644
index 0000000..6e76d5c
--- /dev/null
+++ b/generation_config.json
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+{
+  "_from_model_config": true,
+  "bos_token_id": 128000,
+  "do_sample": true,
+  "eos_token_id": 128001,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.50.0"
+}
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diff --git a/special_tokens_map.json b/special_tokens_map.json
new file mode 100644
index 0000000..344c826
--- /dev/null
+++ b/special_tokens_map.json
@@ -0,0 +1,23 @@
+{
+  "bos_token": {
+    "content": "<|begin_of_text|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|eot_id|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|eot_id|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}
diff --git a/tokenizer.json b/tokenizer.json
new file mode 100644
index 0000000..1c1d8d5
--- /dev/null
+++ b/tokenizer.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6b9e4e7fb171f92fd137b777cc2714bf87d11576700a1dcd7a399e7bbe39537b
+size 17209920
diff --git a/tokenizer_config.json b/tokenizer_config.json
new file mode 100644
index 0000000..8ae1bc6
--- /dev/null
+++ b/tokenizer_config.json
@@ -0,0 +1,2064 @@
+{
+  "added_tokens_decoder": {
+    "128000": {
+      "content": "<|begin_of_text|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128001": {
+      "content": "<|end_of_text|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+  },
+  "bos_token": "<|begin_of_text|>",
+  "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n    {%- set date_string = \"26 Jul 2024\" %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content']|trim %}\n    {%- set messages = messages[1:] %}\n{%- else %}\n    {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n    {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n    {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\n\"}}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n    {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n    {#- Extract the first user message so we can plug it in here #}\n    {%- if messages | length != 0 %}\n        {%- set first_user_message = messages[0]['content']|trim %}\n        {%- set messages = messages[1:] %}\n    {%- else %}\n        {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n    {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n    {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n    {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n    {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {%- if not message.tool_calls|length == 1 %}\n            {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n        {%- endif %}\n        {%- set tool_call = message.tool_calls[0].function %}\n        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n            {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n            {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n            {%- for arg_name, arg_val in tool_call.arguments | items %}\n                {{- arg_name + '=\"' + arg_val + '\"' }}\n                {%- if not loop.last %}\n                    {{- \", \" }}\n                {%- endif %}\n                {%- endfor %}\n            {{- \")\" }}\n        {%- else  %}\n            {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n            {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n            {{- '\"parameters\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- \"}\" }}\n        {%- endif %}\n        {%- if builtin_tools is defined %}\n            {#- This means we're in ipython mode #}\n            {{- \"<|eom_id|>\" }}\n        {%- else %}\n            {{- \"<|eot_id|>\" }}\n        {%- endif %}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n        {%- if message.content is mapping or message.content is iterable %}\n            {{- message.content | tojson }}\n        {%- else %}\n            {{- message.content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 131072,
+  "pad_token": "<|eot_id|>",
+  "tokenizer_class": "PreTrainedTokenizer"
+}
diff --git a/trainer_state.json b/trainer_state.json
new file mode 100644
index 0000000..f24af12
--- /dev/null
+++ b/trainer_state.json
@@ -0,0 +1,409 @@
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