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
| # 🚀 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** | |
| 1. Go to https://github.com/organizations/my-ai-stack/repositories/new | |
| 2. Repository name: `stack-2.9` | |
| 3. Description: "Open-source voice-enabled AI coding assistant based on Qwen2.5-Coder-32B" | |
| 4. Choose: | |
| - ☑ Public (recommended for open source) | |
| - ☐ Private (if you want to restrict access) | |
| - ☑ Initialize with a README? **NO** (we already have one) | |
| 5. Click "Create repository" | |
| **Option B: Via GitHub CLI** (if you have `gh` installed) | |
| ```bash | |
| 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: | |
| ```bash | |
| 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 | |
| ```bash | |
| # 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) | |
| 1. Go to repo Settings → Pages | |
| 2. Source: "GitHub Actions" or "main branch /docs folder" | |
| 3. Save → 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 → Features → enable Discussions, Projects, Wiki as needed | |
| #### Set Up GitHub Actions Secrets (if needed) | |
| If CI/CD needs additional secrets (like Hugging Face token): | |
| 1. Settings → Secrets and variables → Actions | |
| 2. Add: | |
| - `HF_TOKEN` - Hugging Face API token | |
| - `OPENROUTER_API_KEY` - OpenRouter API key (for testing) | |
| #### Add Collaborators | |
| Invite team members: | |
| - Settings → Collaborators and teams → 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: | |
| ```bash | |
| 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 | |
| 1. ✅ Create GitHub repo and push code | |
| 2. ✅ Enable issues, discussions, wiki | |
| 3. ▶️ Start training on GPU (if available) | |
| 4. ▶️ Push trained model to Hugging Face | |
| 5. ▶️ Submit to OpenRouter | |
| 6. ▶️ Create community (Discord) | |
| 7. ▶️ Iterate on training data and evaluation | |
| --- | |
| **Ready?** Run the git commands above and let me know if you hit any issues! |