sartajbhuvaji
/

Legal-Llama-3.2-3B-Instruct

@@ -1,199 +1,87 @@
 ---
-library_name: transformers
-tags: []
 ---
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 ---
+language:
+- en
+tags:
+- llama-2
+- peft
+- qlora
+- legal-ai
+- fine-tuning
+license: apache-2.0
+datasets:
+- nisaar/LLAMA2_Legal_Dataset_4.4k_Instructions
+base_model: meta-llama/Llama-3.2-3B-Instruct
+model-index:
+- name: Legal-Llama-3.2-3B-Instruct
+  results: []
+pipeline_tag: text-generation
 ---
+# sartajbhuvaji/Legal-Llama-3.2-3B-Instruct
+This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct using QLoRA.
+## Model description
+Fine-tuned Llama 2 model for legal tasks
 ## Training Details
+- Base Model: meta-llama/Llama-3.2-3B-Instruct
+- Training Method: QLoRA (Quantized Low-Rank Adaptation)
+- Framework: PEFT (Parameter-Efficient Fine-Tuning)
+- Dataset: nisaar/LLAMA2_Legal_Dataset_4.4k_Instructions
+- Training Date: 2024-12-29
+## Intended Uses
+This model is designed for legal domain tasks and should be used in accordance with the base model's intended use cases and limitations.
+## Usage
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+# Load base model
+model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B-Instruct")
+# Load adapter
+model = PeftModel.from_pretrained(
+    model,
+    "sartajbhuvaji/Legal-Llama-3.2-3B-Instruct"
+)
+# Load tokenizer
+tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.2-3B-Instruct")
+# Format prompt
+prompt = "<s> [INST] Your prompt here [/INST]"
+inputs = tokenizer(prompt, return_tensors="pt")
+# Generate
+outputs = model.generate(**inputs, max_length=512)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+## Limitations
+- This is a fine-tuned model and inherits the limitations of the base model
+- The model's performance is limited to the scope and quality of the training dataset
+- Legal advice generated by the model should not be considered as professional legal counsel
+## Training Hyperparameters
+- Learning rate: 2e-4
+- Epochs: 3
+- Batch size: 4
+- LoRA rank: 32
+- LoRA alpha: 16
+- Gradient accumulation steps: 4
+## Citation
+```bibtex
+@misc{your-model-name,
+  author = {Your Name},
+  title = {Your Model Title},
+  year = {2024},
+  publisher = {HuggingFace},
+  journal = {HuggingFace Hub},
+  howpublished = {\url{https://huggingface.co/sartajbhuvaji/Legal-Llama-3.2-3B-Instruct}}
+}
+```