Text Generation
Transformers
Safetensors
gpt_bigcode
starcoder
agentic-coding
merged
conversational
text-generation-inference
Instructions to use Colby/starcoder-7b-agent-0.6-merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Colby/starcoder-7b-agent-0.6-merged with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Colby/starcoder-7b-agent-0.6-merged") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Colby/starcoder-7b-agent-0.6-merged") model = AutoModelForCausalLM.from_pretrained("Colby/starcoder-7b-agent-0.6-merged") 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 Colby/starcoder-7b-agent-0.6-merged with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Colby/starcoder-7b-agent-0.6-merged" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Colby/starcoder-7b-agent-0.6-merged", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Colby/starcoder-7b-agent-0.6-merged
- SGLang
How to use Colby/starcoder-7b-agent-0.6-merged 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 "Colby/starcoder-7b-agent-0.6-merged" \ --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": "Colby/starcoder-7b-agent-0.6-merged", "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 "Colby/starcoder-7b-agent-0.6-merged" \ --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": "Colby/starcoder-7b-agent-0.6-merged", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Colby/starcoder-7b-agent-0.6-merged with Docker Model Runner:
docker model run hf.co/Colby/starcoder-7b-agent-0.6-merged
Upload README.md with huggingface_hub
Browse files
README.md
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---
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base_model: Colby/starcoder-7b-agent-0.2-merged
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tags:
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- transformers
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- safetensors
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- starcoder
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- agentic-coding
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- merged
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---
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# starcoder-7b-agent-0.6-merged
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Merged (LoRA-flattened) version of [Colby/starcoder-7b-agent-0.6](https://huggingface.co/Colby/starcoder-7b-agent-0.5).
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Used as the base model for the next round of fine-tuning.
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Vocab: 49162 (6 new special tokens: `<tool_call>`, `</tool_call>`, `<tool_response>`,
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`</tool_response>`, `<think>`, `</think>`).
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Chat format: StarCoderChat (`<|system|>`, `<|user|>`, `<|assistant|>`, `<|end|>`)
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with `<think>...</think>` and `<tool_call>`/`<tool_response>` blocks.
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