Update README.md

README.md

@@ -1,30 +1,56 @@
 ---
-{}
+license: llama3.1
 ---
----
-    license: apache-2.0
+# BRAG-Llama-3.1-8b-v0.1 Model Card
+
+## Model Description
+
+BRAG-Llama-3.1-8b-v0.1 is part of the BRAG series of SLMs (Small Language Models) specifically trained for RAG (Retrieval-Augmented Generation) tasks. This model is an instruct finetuning of the Llama-3.1-8b-instruct base model. For more details about BRAG series, please refer to our blogpost.
+
+## Key Features
+
+- **Model Size**: 8 billion parameters
+- **Context Length**: Supports up to 128k tokens
+- **Language**: Trained and evaluated for English, but the base model has multi-lingual capabilities
+
+## Performance
+
+- **ChatRAG-Bench (all)**: 51.70
+
+## How to Use
+
+[Include information on how to use the model]
+
+## Use Cases
+
+BRAG-Llama-3-8b-v0.1 is designed for RAG (Retrieval-Augmented Generation) tasks, making it suitable for applications that require processing and generating responses based on contexts, chats with tables and text, such as:
+
+	1.	Question-answering systems with tables and text.
+	2.	Contextual conversational chat.
+
+## Limitations
+
+As with all LLMs, users should be aware of potential biases and limitations. Always verify important information and use the model responsibly.
+
+## Citation
 
-    Usage:
+To cite this model, please use the following:
 
-    ```python
-    !pip install -qU transformers accelerate
+```bibtex
+@misc{BRAG-Llama-3-8b-v0.1,
+  title = {BRAG-Llama-3-8b-v0.1},
+  year = {2024},
+  publisher = {HuggingFace},
+  url = {[https://huggingface.co/maximalists/BRAG-Llama-3-8b-v0.1](https://huggingface.co/maximalists/BRAG-v0.43)},
+author = {Pratik Bhavsar and Ravi Theja}
+}
+```
 
-    from transformers import AutoTokenizer
-    import transformers
-    import torch
+## Model Access
 
-    model = model_name
-    messages = [{"role": "user", "content": "What is a large language model?"}]
+The model is available on the HuggingFace Model Hub:
+[https://huggingface.co/maximalists/BRAG-Llama-3-8b-v0.1](https://huggingface.co/maximalists/BRAG-Llama-3-8b-v0.1)
 
-    tokenizer = AutoTokenizer.from_pretrained(model)
-    prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-    pipeline = transformers.pipeline(
-        "text-generation",
-        model=model,
-        torch_dtype=torch.float16,
-        device_map="auto",
-    )
+## Additional Information
 
-    outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.1, top_k=50, top_p=0.95)
-    print(outputs[0]["generated_text"])
-    ```
+For more details on the BRAG series and updates, please refer to the official blogpost.