Update README.md

README.md

@@ -4,29 +4,22 @@ language:
 - ar
 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 Card for BiMediX-Bilingual
 
 ### Model Details
 - **Name:** BiMediX
 - **Version:** 1.0
 - **Type:** Bilingual Medical Mixture of Experts Large Language Model (LLM)
-- **Languages:** English, Arabic
+- **Languages:** 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.
+- **Training Data:** BiMed1.3M-Arabic, an arabic dataset with diverse medical interactions.
 
 ### Intended Use
 - **Primary Use:** Medical interactions in both English and Arabic.
@@ -42,7 +35,7 @@ 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."
+text = "مرحبًا بيميديكس! لقد كنت أعاني من التعب المتزايد في الأسبوع الماضي."
 inputs = tokenizer(text, return_tensors="pt")
 
 outputs = model.generate(**inputs, max_new_tokens=500)
@@ -50,12 +43,11 @@ 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:**
+- **Dataset:** BiMed1.3M-Arabic.
+- **QLoRA Adaptation:** Implements a low-rank adaptation technique, incorporating learnable low-rank adapter weights into the experts and the routing network. This results in training about 4% of the original parameters.
+- **Training Resources:** The model underwent training on the Arabic corpus.
 
 ### Model Performance
-- **Benchmarks:** Outperforms the baseline model and Jais-30B in medical evaluations.
 
 | **Model**                         | **CKG** | **CBio** | **CMed** | **MedGen** | **ProMed** | **Ana** | **MedMCQA** | **MedQA** | **PubmedQA** | **AVG** |
 |-----------|------------|-----------|-----------|-------------|-------------|---------|-------------|-----------|--------------|---------|
@@ -75,4 +67,4 @@ print(tokenizer.decode(outputs[0], skip_special_tokens=True))
 
 ### 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)**
+**Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI)**