Text Generation
Transformers
English
qwen2
code-generation
python
fine-tuning
Qwen
tools
agent-framework
multi-agent
conversational
Eval Results (legacy)
Instructions to use my-ai-stack/Stack-2-9-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use my-ai-stack/Stack-2-9-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="my-ai-stack/Stack-2-9-finetuned") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("my-ai-stack/Stack-2-9-finetuned") model = AutoModelForCausalLM.from_pretrained("my-ai-stack/Stack-2-9-finetuned") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use my-ai-stack/Stack-2-9-finetuned with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "my-ai-stack/Stack-2-9-finetuned" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "my-ai-stack/Stack-2-9-finetuned", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/my-ai-stack/Stack-2-9-finetuned
- SGLang
How to use my-ai-stack/Stack-2-9-finetuned with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "my-ai-stack/Stack-2-9-finetuned" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "my-ai-stack/Stack-2-9-finetuned", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "my-ai-stack/Stack-2-9-finetuned" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "my-ai-stack/Stack-2-9-finetuned", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use my-ai-stack/Stack-2-9-finetuned with Docker Model Runner:
docker model run hf.co/my-ai-stack/Stack-2-9-finetuned
| [build-system] | |
| requires = ["setuptools>=61.0", "wheel"] | |
| build-backend = "setuptools.build_meta" | |
| [project] | |
| name = "stack-2.9" | |
| version = "0.1.0" | |
| description = "AI coding assistant with pattern memory and tool calling" | |
| readme = "README.md" | |
| license = {text = "MIT"} | |
| requires-python = ">=3.10" | |
| dependencies = [ | |
| "transformers>=4.40.0", | |
| "peft>=0.10.0", | |
| "accelerate>=0.34.0", | |
| "datasets>=3.0.0", | |
| "torch>=2.2.0", | |
| "pyyaml>=6.0", | |
| "fastapi>=0.115.0", | |
| "uvicorn[standard]>=0.30.0", | |
| "pydantic>=2.0.0", | |
| ] | |
| [project.optional-dependencies] | |
| dev = [ | |
| "ruff>=0.8.0", | |
| "black>=24.0.0", | |
| "mypy>=1.0.0", | |
| "pytest>=8.0.0", | |
| ] | |
| [tool.ruff] | |
| line-length = 100 | |
| target-version = "py310" | |
| [tool.ruff.lint] | |
| select = ["E", "F", "I", "N", "W", "UP", "B"] | |
| ignore = ["E501"] | |
| [tool.black] | |
| line-length = 100 | |
| target-version = ["py310"] | |
| [tool.mypy] | |
| python_version = "3.10" | |
| warn_return_any = true | |
| warn_unused_ignores = true | |
| [tool.pytest.ini_options] | |
| testpaths = ["tests"] | |