Update README.md

README.md

@@ -2,89 +2,13 @@
 license: mit
 language:
 - en
-base_model:
-- ContactDoctor/Bio-Medical-MultiModal-Llama-3-8B-V1
-pipeline_tag: text-generation
-tags:
-- biology
-- medical
----
-
-# Model Card for Bio-Medical-Llama-3-8B-V1
-
-This model is a fine-tuned version of **Bio-Medical-Llama-3-8B** for generating text related to biomedical knowledge. It is designed to assist in answering health and medical queries, serving as a robust tool for both healthcare professionals and general users.
-
----
-
-## Model Details
-
-### Model Description
-
-- **Developed by:** ContactDoctor
-- **Funded by:** ContactDoctor Research Lab
-- **Model type:** Text Generation
-- **Language(s) (NLP):** English
-- **License:** MIT
-- **Finetuned from model:** Bio-Medical-MultiModal-Llama-3-8B
-
-This model was created to address the need for accurate, conversational assistance in healthcare, biology, and medical science.
-
----
-
-## Uses
-
-### Direct Use
-
-Users can employ the model to generate responses to biomedical questions, explanations of medical concepts, and general healthcare advice.
-
-### Downstream Use
-
-This model can be further fine-tuned for specific tasks, such as diagnosis support, clinical decision-making, and patient education.
-
-### Out-of-Scope Use
-
-The model should not be used as a substitute for professional medical advice, emergency assistance, or detailed medical diagnoses.
-
----
-
-## Bias, Risks, and Limitations
-
-While the model is trained on extensive biomedical data, it might not cover every condition or the latest advancements. Users are advised to treat responses as informational rather than authoritative.
-
-### Recommendations
-
-- Use this model for general guidance, not as a substitute for professional advice.
-- Regularly review updates and improvements for the latest accuracy enhancements.
-
----
-
-## How to Get Started with the Model
-
-You can use the model through the Hugging Face API or locally as shown in the example below.
-
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
-
-# Load the model and tokenizer
-tokenizer = AutoTokenizer.from_pretrained("ContactDoctor/Bio-Medical-Llama-3-8B-V1")
-model = AutoModelForCausalLM.from_pretrained("ContactDoctor/Bio-Medical-Llama-3-8B-V1")
-
-# Initialize the pipeline
-generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
-
-# Generate a response
-response = generator("What is hypertension?", max_length=100)
-print(response[0]["generated_text"])
----
-license: mit
-language:
-- en
 base_model: ContactDoctor/Bio-Medical-MultiModal-Llama-3-8B-V1
 pipeline_tag: text-generation
 tags:
 - biology
 - medical
 - fine-tuning
+library_name: transformers
 ---
 
 # Model Card for Fine-Tuned Bio-Medical-Llama-3-8B