Update README.md

README.md

@@ -6,8 +6,73 @@ metrics:
 - accuracy
 ---
 
+---
+language:
+- en
+- ar
+metrics:
+- accuracy
+pipeline_tag: text-generation
+tags:
+- medical
+license: cc-by-nc-sa-4.0
+---
+
+## Model Card for BiMediX
+
+### Model Details
+- **Name:** BiMediX
+- **Version:** 1.0
+- **Type:** Bilingual Medical Mixture of Experts Large Language Model (LLM)
+- **Languages:** English, Arabic
+- **Model Architecture:** [Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1)
+- **Training Data:** BiMed1.3M, a bilingual dataset with diverse medical interactions.
+
+### Intended Use
+- **Primary Use:** Medical interactions in both English and Arabic.
+- **Capabilities:** MCQA, closed QA and chats.
+
+## Getting Started
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "BiMediX/BiMediX-Ara"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+
+text = "Hello BiMediX! I've been experiencing increased tiredness in the past week."
+inputs = tokenizer(text, return_tensors="pt")
+
+outputs = model.generate(**inputs, max_new_tokens=500)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+### Training Procedure
+- **Dataset:** Semi-automated English-to-Arabic translation with human refinement.
+- **Training Resources:** 632 million healthcare specialized tokens.
+- **Evaluation:**
+
+### Model Performance
+- **Benchmarks:** Outperforms the baseline model and Jais-30B in medical evaluations.
+
 | **Model**                         | **CKG** | **CBio** | **CMed** | **MedGen** | **ProMed** | **Ana** | **MedMCQA** | **MedQA** | **PubmedQA** | **AVG** |
 |-----------|------------|-----------|-----------|-------------|-------------|---------|-------------|-----------|--------------|---------|
 | Jais-30B  | 52.1       | 50.7      | 40.5      | 49.0        | 39.3        | 43.0    | 37.0        | 28.8      | 74.6         | 46.1    |
 | BiMediX (Arabic) | 60.0 | 54.9 | **55.5** | 58.0 | **58.1** | 49.6 | 46.0 | 40.2 | 76.6 | 55.4 |
-| **BiMediX (Bilingual)** | **63.8** | **57.6** | 52.6 | **64.0** | 52.9 | **50.4** | **49.1** | **47.3** | **78.4** | **56.5** |
+| **BiMediX (Bilingual)** | **63.8** | **57.6** | 52.6 | **64.0** | 52.9 | **50.4** | **49.1** | **47.3** | **78.4** | **56.5** |
+
+### Limitations
+- Potential issues: hallucinations, toxicity, stereotypes.
+- Medical diagnoses and recommendations require human evaluation.
+
+### Safety and Ethical Considerations
+- **Usage:** Research purposes only.
+
+### Accessibility
+- **Availability:** [BiMediX GitHub Repository](https://github.com/mbzuai-oryx/BiMediX).
+
+### Authors
+Sara Pieri, Sahal Shaji Mullappilly, Fahad Shahbaz Khan, Rao Muhammad Anwer Salman Khan, Timothy Baldwin, Hisham Cholakkal  
+**Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI)**