Create README.md

README.md

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+---
+base_model: allenai/OLMo-1B-hf
+library_name: peft
+---
+
+# OLMo Code Python3 Text-Only Model
+
+This is a LoRA adapter fine-tuned on the OLMo-1B model for Python 3 code generation tasks.
+
+## Model Details
+
+- **Base Model:** allenai/OLMo-1B-hf
+- **Model Type:** LoRA Adapter
+- **Task:** Causal Language Modeling for Python 3 code
+- **Language:** Python 3
+- **License:** MIT
+- **Fine-tuned by:** dipikakhullar
+
+## Model Description
+
+This model is a LoRA adapter that has been fine-tuned on Python 3 code data. It extends the capabilities of the base OLMo-1B model specifically for Python code generation tasks.
+
+### LoRA Configuration
+
+- **LoRA Type:** LORA
+- **LoRA Alpha:** 16
+- **LoRA Dropout:** 0.05
+- **LoRA Rank (r):** 8
+- **Target Modules:** down_proj, q_proj, v_proj, up_proj, k_proj, gate_proj, o_proj
+- **Task Type:** CAUSAL_LM
+
+## Uses
+
+### Direct Use
+
+This model is intended for Python 3 code generation tasks. It can be used to:
+- Generate Python code completions
+- Assist with code writing
+- Provide code suggestions
+
+### Downstream Use
+
+The model can be further fine-tuned for specific Python programming tasks or integrated into code generation applications.
+
+### Out-of-Scope Use
+
+This model is specifically designed for Python 3 code generation and may not perform well for:
+- Other programming languages
+- Natural language tasks
+- Non-code related tasks
+
+## How to Get Started with the Model
+
+```python
+from peft import PeftModel, PeftConfig
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the base model and tokenizer
+base_model = AutoModelForCausalLM.from_pretrained("allenai/OLMo-1B-hf")
+tokenizer = AutoTokenizer.from_pretrained("allenai/OLMo-1B-hf")
+
+# Load the LoRA adapter
+model = PeftModel.from_pretrained(base_model, "dipikakhullar/olmo-code-python3-text-only")
+
+# Example usage
+prompt = "def fibonacci(n):"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=100, temperature=0.7)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Training Details
+
+### Training Data
+
+The model was fine-tuned on cleaned Python 3 code data specifically prepared for language model training.
+
+### Training Procedure
+
+- **Base Model:** allenai/OLMo-1B-hf
+- **Fine-tuning Method:** LoRA (Low-Rank Adaptation)
+- **Checkpoint:** checkpoint-6000
+
+## Model Card Contact
+
+- **Author:** dipikakhullar
+- **Repository:** https://huggingface.co/dipikakhullar/olmo-code-python3-text-only
+
+## Framework versions
+
+- PEFT 0.7.1
+- Transformers