Text Generation
Transformers
Safetensors
code
gpt_neox
causal-lm
Eval Results (legacy)
text-generation-inference
4-bit precision
gptq
Instructions to use TheBloke/stablecode-completion-alpha-3b-4k-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheBloke/stablecode-completion-alpha-3b-4k-GPTQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TheBloke/stablecode-completion-alpha-3b-4k-GPTQ")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TheBloke/stablecode-completion-alpha-3b-4k-GPTQ") model = AutoModelForCausalLM.from_pretrained("TheBloke/stablecode-completion-alpha-3b-4k-GPTQ") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use TheBloke/stablecode-completion-alpha-3b-4k-GPTQ with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TheBloke/stablecode-completion-alpha-3b-4k-GPTQ" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/stablecode-completion-alpha-3b-4k-GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TheBloke/stablecode-completion-alpha-3b-4k-GPTQ
- SGLang
How to use TheBloke/stablecode-completion-alpha-3b-4k-GPTQ 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 "TheBloke/stablecode-completion-alpha-3b-4k-GPTQ" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/stablecode-completion-alpha-3b-4k-GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "TheBloke/stablecode-completion-alpha-3b-4k-GPTQ" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/stablecode-completion-alpha-3b-4k-GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TheBloke/stablecode-completion-alpha-3b-4k-GPTQ with Docker Model Runner:
docker model run hf.co/TheBloke/stablecode-completion-alpha-3b-4k-GPTQ
Update base_model formatting
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datasets:
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inference: false
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language:
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license: apache-2.0
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model-index:
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- name: stabilityai/stablecode-completion-alpha-3b-4k
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results:
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name: HumanEval
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type: openai_humaneval
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metrics:
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type: pass@1
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value: 0.1768
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verified: false
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type: pass@10
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value: 0.2701
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verified: false
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task:
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type: text-generation
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model_creator: StabilityAI
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model_link: https://huggingface.co/stabilityai/stablecode-completion-alpha-3b-4k
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model_name: Stablecode Completion Alpha 3B 4K
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model_type: gptneox
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quantized_by: TheBloke
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tags:
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- causal-lm
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---
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<!-- header start -->
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---
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language:
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- code
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license: apache-2.0
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tags:
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- causal-lm
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datasets:
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- bigcode/starcoderdata
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inference: false
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model_creator: StabilityAI
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model_link: https://huggingface.co/stabilityai/stablecode-completion-alpha-3b-4k
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model_type: gptneox
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quantized_by: TheBloke
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base_model: stabilityai/stablecode-completion-alpha-3b-4k
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model-index:
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- name: stabilityai/stablecode-completion-alpha-3b-4k
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results:
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- task:
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type: text-generation
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dataset:
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name: HumanEval
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type: openai_humaneval
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metrics:
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- type: pass@1
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value: 0.1768
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name: pass@1
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verified: false
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- type: pass@10
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value: 0.2701
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name: pass@10
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verified: false
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---
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