Text Generation
Transformers
Safetensors
English
code
llama
debugging
instruct
lightweight
iranian-company
neuracoder
debugger
bug-fixing
code-repair
conversational
text-generation-inference
Instructions to use neuracoder/neuradebugger-Micro-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neuracoder/neuradebugger-Micro-1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="neuracoder/neuradebugger-Micro-1b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("neuracoder/neuradebugger-Micro-1b") model = AutoModelForCausalLM.from_pretrained("neuracoder/neuradebugger-Micro-1b") 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 Settings
- vLLM
How to use neuracoder/neuradebugger-Micro-1b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "neuracoder/neuradebugger-Micro-1b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "neuracoder/neuradebugger-Micro-1b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/neuracoder/neuradebugger-Micro-1b
- SGLang
How to use neuracoder/neuradebugger-Micro-1b 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 "neuracoder/neuradebugger-Micro-1b" \ --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": "neuracoder/neuradebugger-Micro-1b", "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 "neuracoder/neuradebugger-Micro-1b" \ --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": "neuracoder/neuradebugger-Micro-1b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use neuracoder/neuradebugger-Micro-1b with Docker Model Runner:
docker model run hf.co/neuracoder/neuradebugger-Micro-1b
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Unlike general code generation models that often produce new bugs, NeuraDebugger-Micro focuses exclusively on **finding and fixing errors** in existing code. It understands exception traces, logical flaws, edge cases, and common pitfalls across 12 programming languages. Despite its tiny size, it runs on laptops, CPU‑only machines, and even Raspberry Pi, giving every developer an expert debugger at their fingertips.
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## 📞 Contact Neuracoder Team
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- **Website:** neuracoder.net (coming soon)
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- **Email:** info@neuracoder.net
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- **Telegram:** @Neuracoder
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- **GitHub:** github.com/neura_coder
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