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
π Pushing to GitHub (my-ai-stack/stack-2.9)
This guide walks through creating the repository on GitHub and pushing the local code.
Prerequisites
- You have a GitHub account with admin access to the my-ai-stack organization
- Git is installed locally
- You have configured SSH or HTTPS credentials for GitHub
Steps
1. Create the Repository on GitHub
Option A: Via Web Interface
- Go to https://github.com/organizations/my-ai-stack/repositories/new
- Repository name:
stack-2.9 - Description: "Open-source voice-enabled AI coding assistant based on Qwen2.5-Coder-32B"
- Choose:
- β Public (recommended for open source)
- β Private (if you want to restrict access)
- β Initialize with a README? NO (we already have one)
- Click "Create repository"
Option B: Via GitHub CLI (if you have gh installed)
gh repo create my-ai-stack/stack-2.9 \
--public \
--description "Open-source voice-enabled AI coding assistant based on Qwen2.5-Coder-32B" \
--source . \
--remote origin
2. Connect Local Repository to GitHub
From the stack-2.9 directory:
cd /Users/walidsobhi/.openclaw/workspace/stack-2.9
# If you used Option B above, this is already done. For Option A:
git init
git add .
git commit -m "feat: initial Stack 2.9 release
- Training pipeline with LoRA fine-tuning
- vLLM deployment with Docker
- Voice integration module
- Evaluation suite with benchmarks
- 519 training examples with advanced patterns
- Complete documentation and CI/CD"
# Add GitHub remote (replace with your actual repo URL)
git remote add origin https://github.com/my-ai-stack/stack-2.9.git
# Or via SSH (if you have SSH keys set up):
# git remote add origin git@github.com:my-ai-stack/stack-2.9.git
3. Push to GitHub
# Push main branch
git branch -M main
git push -u origin main
# Push all tags (if any)
git push --tags
4. Verify
Visit: https://github.com/my-ai-stack/stack-2.9
You should see all files:
- README.md with badges
- All subdirectories (training, deploy, voice, docs, eval)
- Documentation
- Makefile for easy builds
5. Post-Push Setup (Optional but Recommended)
Enable GitHub Pages (for docs)
- Go to repo Settings β Pages
- Source: "GitHub Actions" or "main branch /docs folder"
- Save β docs will be at https://my-ai-stack.github.io/stack-2.9/
Add Repository Topics
Add these topics to improve discoverability:
ai,llm,coding-assistant,voice,open-source,qwen,vllm,fine-tuning,training-data,huggingface,openrouter
Configure Repository Features
- Settings β Features β enable Discussions, Projects, Wiki as needed
Set Up GitHub Actions Secrets (if needed)
If CI/CD needs additional secrets (like Hugging Face token):
- Settings β Secrets and variables β Actions
- Add:
HF_TOKEN- Hugging Face API tokenOPENROUTER_API_KEY- OpenRouter API key (for testing)
Add Collaborators
Invite team members:
- Settings β Collaborators and teams β Add people
6. Update OpenRouter Submission
In stack-2.9-docs/OPENROUTER_SUBMISSION.md, update:
- Repository URL:
https://github.com/my-ai-stack/stack-2.9 - Date of submission
- Point of contact
Email the submission to OpenRouter or submit via their form.
7. Share with Community
Once pushed:
- Announce on Discord/Twitter/LinkedIn
- Submit to Hacker News, r/MachineLearning, etc.
- Engage with Hugging Face community
- Reach out to OpenRouter for listing
Troubleshooting
Error: remote: Repository not found.
- Check you have permission to create repos in my-ai-stack org
- Verify you're using the correct org name
- Try SSH instead of HTTPS
Error: remote: Permission to my-ai-stack/stack-2.9.git denied
- You need admin access to the org
- Contact org admin to grant permissions
Large files failing to push
- Training data might be too large (~100MB+)
- Consider using Git LFS for large files:
git lfs install git lfs track "training-data/advanced-patterns/*.jsonl" git add .gitattributes
Hitting GitHub rate limits
- Use SSH instead of HTTPS
- Authenticate properly with gh CLI
Next Steps After Push
- β Create GitHub repo and push code
- β Enable issues, discussions, wiki
- βΆοΈ Start training on GPU (if available)
- βΆοΈ Push trained model to Hugging Face
- βΆοΈ Submit to OpenRouter
- βΆοΈ Create community (Discord)
- βΆοΈ Iterate on training data and evaluation
Ready? Run the git commands above and let me know if you hit any issues!