Create README.md

README.md

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+---
+base_model: meta-llama/meta-llama-3.1-8b-instruct
+tags:
+- llama adapter
+- trl
+- llama3.1 8b
+license: apache-2.0
+language:
+- en
+---
+## Model Overview
+A LoRA (Low-Rank Adaptation) decomposed from base model from base to instruct
+
+## Model Details
+- Base Model: (meta-llama/Llama-3.1-8B) - (meta-llama/Llama-3.1-8B-instruct)
+- Adaptation Method: LoRA
+
+## Training Configuration
+### Training Hyperparameters
+- Rank (r): 16
+- Alpha: 16
+
+### LoRA Configuration
+- Rank (r): 16
+- Alpha: 16
+- Target Modules:
+  - `q_proj` (Query projection)
+  - `k_proj` (Key projection)
+  - `v_proj` (Value projection)
+  - `o_proj` (Output projection)
+  - `up_proj` (Upsampling projection)
+  - `down_proj` (Downsampling projection)
+  - `gate_proj` (Gate projection)
+
+## Usage
+This adapter must be used in conjunction with the base Llama-3.1-8B-instruct model. 
+
+### Loading the Model
+```python
+from peft import PeftModel, PeftConfig
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load base model
+base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-instruct")
+tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-8B-instruct")
+
+# Load LoRA adapter
+model = PeftModel.from_pretrained(base_model, "path_to_adapter")
+```
+
+## Limitations and Biases
+- This adapter might inherits some limitations and biases present in the base Llama-3.1-8B-instruct model