Jerry-lin23
/

deepseek-leetcode-p3

@@ -1,199 +1,156 @@
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 ---
+license: mit
+base_model: deepseek-ai/deepseek-coder-6.7b-base
+tags:
+  - code
+  - leetcode
+  - python
+  - fine-tuned
+  - lora
+  - qlora
+datasets:
+  - LongQ/leetcode_python
+language:
+  - en
+pipeline_tag: text-generation
 ---
+# DeepSeek-Coder-6.7B LeetCode Fine-Tuned
+A fine-tuned version of [DeepSeek-Coder-6.7B-Base](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base) specialized for solving LeetCode-style algorithmic problems in Python.
 ## Model Details
+| Attribute | Value |
+|-----------|-------|
+| **Base Model** | deepseek-ai/deepseek-coder-6.7b-base |
+| **Fine-tuning Method** | QLoRA (4-bit quantization + LoRA) |
+| **Training Data** | [LongQ/leetcode_python](https://huggingface.co/datasets/LongQ/leetcode_python) (2,369 problems) |
+| **Epochs** | 3 |
+| **Hardware** | NVIDIA T4 (16GB VRAM) |
+| **Training Time** | ~5 hours |
+## Performance
+Evaluated on 100 LeetCode problems with automated code execution:
+| Metric | Base Model | Fine-Tuned | Improvement |
+|--------|------------|------------|-------------|
+| **Overall Accuracy** | 24% | 34% | +42% |
+| **Easy Problems** | 30.3% | 52% | +72% |
+| **Medium Problems** | 32.4% | 27.8% | -14% |
+| **Hard Problems** | 9.1% | 28.6% | +214% |
+### Key Findings
+- **Significant gains on Easy and Hard problems** — model learned both fundamental patterns and complex algorithms
+- **Slight regression on Medium** — possible overfitting to extremes of difficulty distribution
+- **Domain-specific data matters** — initial training on general coding data degraded performance
+## Intended Use
+- Solving algorithmic coding challenges
+- LeetCode practice and learning
+- Code generation for competitive programming
+- Educational tool for understanding algorithmic solutions
+## Limitations
+- Optimized specifically for LeetCode-style problems, may not generalize to other coding tasks
+- Python-only (not trained on other languages)
+- May produce syntactically correct but logically incorrect solutions
+- Struggles with problems requiring complex data structure implementations (LinkedList, Trees)
+## How to Use
+### With Hugging Face Transformers
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+model = AutoModelForCausalLM.from_pretrained(
+    "Jerry-lin23/deepseek-leetcode-fp16",
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained("Jerry-lin23/deepseek-leetcode-fp16")
+prompt = """### Problem:
+Given an array of integers nums and an integer target, return indices of the two numbers such that they add up to target.
+### Starter Code:
+```python
+class Solution:
+    def twoSum(self, nums: List[int], target: int) -> List[int]:
+```
+### Solution:
+```python
+"""
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=200, temperature=0.2)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+### With Ollama (Local Deployment)
+1. Convert to GGUF format
+2. Create a Modelfile:
+```
+FROM ./deepseek-leetcode-q8.gguf
+PARAMETER temperature 0.2
+PARAMETER top_p 0.95
+```
+3. Import: `ollama create deepseek-leetcode -f Modelfile`
+4. Run: `ollama run deepseek-leetcode`
 ## Training Details
+### LoRA Configuration
+```python
+LoraConfig(
+    r=16,
+    lora_alpha=32,
+    target_modules=["q_proj", "k_proj", "v_proj", "o_proj", "gate_proj", "up_proj", "down_proj"],
+    lora_dropout=0.05,
+    bias="none",
+    task_type="CAUSAL_LM"
+)
+```
+### Training Arguments
+```python
+SFTConfig(
+    num_train_epochs=3,
+    per_device_train_batch_size=1,
+    gradient_accumulation_steps=8,
+    learning_rate=2e-4,
+    warmup_ratio=0.03,
+    fp16=True,
+    gradient_checkpointing=True,
+    max_seq_length=2048,
+    dataset_text_field="text"
+)
+```
+## Citation
+```bibtex
+@misc{deepseek-leetcode-finetuned,
+  author = {Jerry Lin},
+  title = {DeepSeek-Coder-6.7B LeetCode Fine-Tuned},
+  year = {2024},
+  publisher = {Hugging Face},
+  url = {https://huggingface.co/Jerry-lin23/deepseek-leetcode-fp16}
+}
+```
+## Links
+- 📊 [Benchmark Repository](https://github.com/jerrylin-23/DeepSeek-LeetCode-Oriented-Training)
+- 🤗 [Base Model](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base)
+- 📚 [Training Dataset](https://huggingface.co/datasets/LongQ/leetcode_python)