Update README.md

README.md

@@ -17,6 +17,125 @@ base_model: Ellbendls/llama-3.2-3b-chat-doctor
 This model was converted to GGUF format from [`Ellbendls/llama-3.2-3b-chat-doctor`](https://huggingface.co/Ellbendls/llama-3.2-3b-chat-doctor) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/Ellbendls/llama-3.2-3b-chat-doctor) for more details on the model.
 
+---
+Model details:
+-
+Llama-3.2-3B-Chat-Doctor is a specialized medical question-answering model based on the Llama 3.2 3B architecture. This model has been fine-tuned specifically for providing accurate and helpful responses to medical-related queries.
+
+    Developed by: Ellbendl Satria
+    Model type: Language Model (Conversational AI)
+    Language: English
+    Base Model: Meta Llama-3.2-3B-Instruct
+    Model Size: 3 Billion Parameters
+    Specialization: Medical Question Answering
+    License: llama3.2
+
+Model Capabilities
+
+    Provides informative responses to medical questions
+    Assists in understanding medical terminology and health-related concepts
+    Offers preliminary medical information (not a substitute for professional medical advice)
+
+Direct Use
+
+This model can be used for:
+
+    Providing general medical information
+    Explaining medical conditions and symptoms
+    Offering basic health-related guidance
+    Supporting medical education and patient communication
+
+Limitations and Important Disclaimers
+
+⚠️ CRITICAL WARNINGS:
+
+    NOT A MEDICAL PROFESSIONAL: This model is NOT a substitute for professional medical advice, diagnosis, or treatment.
+    Always consult a qualified healthcare provider for medical concerns.
+    The model's responses should be treated as informational only and not as medical recommendations.
+
+Out-of-Scope Use
+
+The model SHOULD NOT be used for:
+
+    Providing emergency medical advice
+    Diagnosing specific medical conditions
+    Replacing professional medical consultation
+    Making critical healthcare decisions
+
+Bias, Risks, and Limitations
+Potential Biases
+
+    May reflect biases present in the training data
+    Responses might not account for individual patient variations
+    Limited by the comprehensiveness of the training dataset
+
+Technical Limitations
+
+    Accuracy is limited to the knowledge in the training data
+    May not capture the most recent medical research or developments
+    Cannot perform physical examinations or medical tests
+
+Recommendations
+
+    Always verify medical information with professional healthcare providers
+    Use the model as a supplementary information source
+    Be aware of potential inaccuracies or incomplete information
+
+Training Details
+Training Data
+
+    Source Dataset: ruslanmv/ai-medical-chatbot
+    Base Model: Meta Llama-3.2-3B-Instruct
+
+Training Procedure
+
+[Provide details about the fine-tuning process, if available]
+
+    Fine-tuning approach
+    Computational resources used
+    Training duration
+    Specific techniques applied during fine-tuning
+
+How to Use the Model
+Hugging Face Transformers
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "Ellbendls/llama-3.2-3b-chat-doctor"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Example usage
+input_text = "I had a surgery which ended up with some failures. What can I do to fix it?"
+
+# Prepare inputs with explicit padding and attention mask
+inputs = tokenizer(input_text, return_tensors="pt", padding=True, truncation=True)
+
+# Generate response with more explicit parameters
+outputs = model.generate(
+    input_ids=inputs['input_ids'], 
+    attention_mask=inputs['attention_mask'],
+    max_new_tokens=150,  # Specify max new tokens to generate
+    do_sample=True,      # Enable sampling for more diverse responses
+    temperature=0.7,     # Control randomness of output
+    top_p=0.9,           # Nucleus sampling to maintain quality
+    num_return_sequences=1  # Number of generated sequences
+)
+
+# Decode the generated response
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+print(response)
+
+Ethical Considerations
+
+This model is developed with the intent to provide helpful, accurate, and responsible medical information. Users are encouraged to:
+
+    Use the model responsibly
+    Understand its limitations
+    Seek professional medical advice for serious health concerns
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)