Justin6657
/

PoPilot

@@ -1,199 +1,51 @@
 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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 ---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-Coder-14B
+tags:
+- code
+- qwen2.5
+- lora-merged
+- fine-tuned
 library_name: transformers
 ---
+# PoPilot - Fine-tuned Qwen2.5-Coder-14B
+This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-14B](https://huggingface.co/Qwen/Qwen2.5-Coder-14B) with LoRA adapters merged.
 ## Model Details
+- **Base Model**: Qwen/Qwen2.5-Coder-14B
+- **Fine-tuning Method**: LoRA (Low-Rank Adaptation)
+- **Training**: Supervised Fine-Tuning (SFT)
+- **Merged**: Full model weights (LoRA merged with base)
+## Usage
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+model = AutoModelForCausalLM.from_pretrained(
+    "Justin6657/PoPilot",
+    torch_dtype="auto",
+    device_map="auto",
+    trust_remote_code=True
+)
+tokenizer = AutoTokenizer.from_pretrained(
+    "Justin6657/PoPilot",
+    trust_remote_code=True
+)
+# Example usage
+prompt = "Write a Python function to calculate fibonacci numbers:"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=200, temperature=0.7)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response)
+```
 ## Training Details
+This model was fine-tuned using LoRA adapters and then merged back into the full model weights.
+Original LoRA checkpoint path: `/net/projects/CLS/DSI_clinic/justin/checkpoint/augmented_train_Qwen2.5-Coder-14B_full-model_repair-synth_repair-simple-phase4`