Update README.md

README.md

@@ -15,12 +15,64 @@ datasets:
 - O1-OPEN/OpenO1-SFT
 ---
 
-This model trains on the base llama model with several open-source datasets.
+> [!TIP]
+> This is an experimental model, so it might not perform well for some prompts and may be sensitive to hyper parameters.
+> It is mainly trained to enhance reasoning capabilities.
 
-WIP
+# khulaifi95/Llama-3.1-8B-Reason-Blend-888k
 
-## Evaluation
 
-## Training
+# 🏆 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_khulaifi95__Llama-3.1-8B-Reason-Blend-888k)
 
-## Usage
+|      Metric       |Value|
+|-------------------|----:|
+|Avg.               |     |
+|IFEval (0-Shot)    |     |
+|BBH (3-Shot)       |     |
+|MATH Lvl 5 (4-Shot)|     |
+|GPQA (0-shot)      |     |
+|MuSR (0-shot)      |     |
+|MMLU-PRO (5-shot)  |     |
+
+# Prompt Template
+
+This model uses `ChatML` prompt template:
+
+```sh
+<|im_start|>system
+{System}
+<|im_end|>
+<|im_start|>user
+{User}
+<|im_end|>
+<|im_start|>assistant
+{Assistant}
+````
+
+# How to use
+
+```python
+
+# Use a pipeline as a high-level helper
+
+from transformers import pipeline
+
+messages = [
+    {"role": "user", "content": "Who are you?"},
+]
+pipe = pipeline("text-generation", model="khulaifi95/Llama-3.1-8B-Reason-Blend-888k")
+pipe(messages)
+
+
+# Load model directly
+
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("khulaifi95/Llama-3.1-8B-Reason-Blend-888k")
+model = AutoModelForCausalLM.from_pretrained("khulaifi95/Llama-3.1-8B-Reason-Blend-888k")
+```
+
+# Ethical Considerations
+
+As with any large language model, users should be aware of potential biases and limitations. We recommend implementing appropriate safeguards and human oversight when deploying this model in production environments.