Bio Medical Llama 3 8B CoT 012025

🚀 Bio-Medical-Llama-3-8B-CoT-012025

This model is a fine - tuned extension of the original Bio - Medical - Llama - 3 - 8B, equipped with advanced reasoning capabilities using a Chain - of - Thought (COT) instruction set, aiming to provide state - of - the - art LLMs for healthcare and life sciences.

🚀 Quick Start

import transformers
import torch

model_id = "ContactDoctor/Bio-Medical-Llama-3-8B-CoT-012025"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

messages = [
    {"role": "system", "content": "You are an expert trained on healthcare and biomedical reasoning."},
    {"role": "user", "content": "What are the differential diagnoses for a 45-year-old male presenting with chest pain?"},
]

prompt = pipeline.tokenizer.apply_chat_template(
        messages,
        tokenize=False,
        add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=256,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.6,
    top_p=0.9,
)
print(outputs[0]["generated_text"][len(prompt):])

✨ Features

• Enhanced Reasoning Abilities: Trained specifically to perform multi - step reasoning and provide accurate, contextually rich responses.
• Compact Model Sizes for Versatility: Includes 1B, 3B, and 8B variants optimized for edge devices and high - performance systems alike.
• Specialized Training Focus: Developed using datasets designed to address the unique challenges of biomedical reasoning and problem - solving.

📦 Installation

The provided README does not contain installation steps, so this section is skipped.

💻 Usage Examples

Basic Usage

import transformers
import torch

model_id = "ContactDoctor/Bio-Medical-Llama-3-8B-CoT-012025"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

messages = [
    {"role": "system", "content": "You are an expert trained on healthcare and biomedical reasoning."},
    {"role": "user", "content": "What are the differential diagnoses for a 45-year-old male presenting with chest pain?"},
]

prompt = pipeline.tokenizer.apply_chat_template(
        messages,
        tokenize=False,
        add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=256,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.6,
    top_p=0.9,
)
print(outputs[0]["generated_text"][len(prompt):])

📚 Documentation

Model Details

Model Description

Bio - Medical - Llama - 3 - 8B - CoT - 012025 represents a leap forward in AI - driven reasoning for the healthcare and life sciences sectors. By incorporating Chain - of - Thought fine - tuning, the model excels at handling complex, multi - step reasoning tasks, making it ideal for scenarios requiring critical thinking and nuanced understanding.

Evaluation Metrics

Bio - Medical - Llama - 3 - 8B - CoT - 012025 demonstrates significant advancements in multi - step reasoning tasks, surpassing its predecessor on HLS benchmarks. However, it is important to note that its performance on evaluation tasks involving multiple - choice questions may be less robust, as it is specifically optimized for reasoning - based challenges.

Intended Uses & Limitations

Bio - Medical - Llama - 3 - 8B - CoT - 012025 is designed for applications requiring high levels of reasoning within the biomedical field, including:

1. Clinical Reasoning: Supporting healthcare professionals in diagnostic and treatment planning.
2. Medical Research: Assisting in hypothesis generation, literature synthesis, and data interpretation.
3. Educational Tools: Providing medical students and professionals with advanced training simulations and problem - solving support.

⚠️ Important Note

• Biases: While efforts were made to minimize bias during training, some biases inherent in the training data may persist.
• Accuracy: This model’s reasoning is based on training data and may not always be up - to - date or contextually perfect. Users should verify critical outputs against authoritative sources.
• Ethical Use: The model is not a substitute for professional medical judgment and should be used responsibly, particularly in clinical decision - making.

Training Hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.00015
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: AdamW with betas=(0.9, 0.98) and epsilon = 1e - 08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.05
• training_steps: 2500
• mixed_precision_training: Native AMP

Framework Versions

• PEFT 0.12.0
• Transformers 4.41.0
• Pytorch 2.1.2
• Datasets 2.21.0
• Tokenizers 0.22.0

Citation

If you use Bio - Medical - Llama - 3 - 8B - CoT - 012025 in your research or applications, please cite it as follows:

@misc{ContactDoctor_Bio - Medical - Llama - 3 - 8B - CoT, author = ContactDoctor, title = {Bio - Medical - CoT: Advanced Reasoning for Healthcare Applications}, year = {2025}, howpublished = {https://huggingface.co/ContactDoctor/Bio - Medical - Llama - 3 - 8B - CoT - 012025}, }

🔧 Technical Details

The provided README does not contain in - depth technical implementation details, so this section is skipped.

📄 License

This model is licensed under the Bio - Medical - Llama - 3 - 8B - CoT - 012025 (Non - Commercial Use Only). Please review the terms and conditions before use.

Contact Information

For further information, inquiries, or issues related to Bio - Medical - Llama - 3 - 8B - CoT - 012025, please contact:

• Email: info@contactdoctor.in
• Website: https://www.contactdoctor.in