| --- |
| license: apache-2.0 |
| language: |
| - en |
| - code |
| tags: |
| - stack-2.9 |
| - open-source |
| - coding-assistant |
| - fine-tuned |
| - qwen |
| - code-generation |
| library_name: transformers |
| --- |
| |
| # Stack 2.9 Fine-Tuned Model |
|
|
| A fine-tuned coding assistant model based on {{base_model}}. |
| |
| ## Model Details |
| |
| | Property | Value | |
| |----------|-------| |
| | Base Model | {{base_model}} | |
| | Training Data | {{training_examples}} examples | |
| | LoRA Rank | {{lora_rank}} | |
| | LoRA Alpha | {{lora_alpha}} | |
| | Max Context Length | {{max_context_length}} | |
| | License | Apache 2.0 | |
| |
| ## Description |
| |
| Stack 2.9 is a fine-tuned coding assistant model designed for code generation, refactoring, and software development tasks. The model has been fine-tuned on a curated dataset of high-quality code examples and programming tasks. |
| |
| ### Training Details |
| |
| - **Dataset**: {{training_examples}} examples from diverse programming domains |
| - **Fine-tuning Method**: LoRA (Low-Rank Adaptation) |
| - **LoRA Configuration**: rank={{lora_rank}}, alpha={{lora_alpha}} |
| - **Base Model**: {{base_model}} |
| |
| ## Benchmarks |
| |
| | Benchmark | Score | |
| |-----------|-------| |
| | HumanEval | {{humaneval_score}} | |
| | MBPP | {{mbpp_score}} | |
| |
| ## Usage |
| |
| ### Using Transformers |
| |
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| model_name = "your-username/stack-2.9-7b" # Replace with your repo |
| tokenizer = AutoTokenizer.from_pretrained(model_name) |
| model = AutoModelForCausalLM.from_pretrained(model_name) |
|
|
| prompt = """Write a Python function to calculate the factorial of a number. |
|
|
| ```python |
| """ |
| |
| inputs = tokenizer(prompt, return_tensors="pt") |
| outputs = model.generate(**inputs, max_new_tokens=200) |
| print(tokenizer.decode(outputs[0])) |
| ``` |
|
|
| ### Using vLLM for Fast Inference |
|
|
| ```python |
| from vllm import LLM, SamplingParams |
| |
| llm = LLM(model="your-username/stack-2.9-7b") |
| sampling_params = SamplingParams(temperature=0.7, max_tokens=200) |
| |
| prompt = "Write a Python function to reverse a string:" |
| outputs = llm.generate(prompt, sampling_params) |
| print(outputs[0].outputs[0].text) |
| ``` |
|
|
| ## Limitations |
|
|
| - The model may generate incorrect code; always verify outputs |
| - Performance may vary across different programming languages |
| - Context window limited to {{max_context_length}} tokens |
|
|
| ## License |
|
|
| This model is licensed under the [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0) license. |
|
|
| ## Citation |
|
|
| If you use this model in your research, please cite: |
|
|
| ```bibtex |
| @misc{stack-2.9, |
| author = {Stack Team}, |
| title = {Stack 2.9: Fine-tuned Coding Assistant}, |
| year = {2025}, |
| publisher = {HuggingFace}, |
| url = {https://huggingface.co/your-username/stack-2.9-7b} |
| } |
| ``` |
|
|
| --- |
|
|
| *Model uploaded via upload_hf.py script* |
