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stablecode-instruct-alpha-3b

Text Generation
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stablecode-instruct-alpha-3b / README.md
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metadata
language:
  - code
tags:
  - causal-lm
model-index:
  - name: stabilityai/stablecode-instruct-alpha-3b
    results:
      - task:
          type: text-generation
        dataset:
          type: openai_humaneval
          name: HumanEval
        metrics:
          - name: pass@1
            type: pass@1
            value: 0.2689
            verified: false
          - name: pass@10
            type: pass@10
            value: 0.3618
            verified: false
license: other
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StableCode-Instruct-Alpha-3B

Model Description

StableCode-Instruct-Alpha-3B is a 3 billion parameter decoder-only instruction tuned code model pre-trained on diverse set of programming languages that topped the stackoverflow developer survey.

Usage

The model is intended to follow instruction to generate code. The dataset used to train the model is formatted in Alpaca format. Get started generating code with StableCode-Instruct-Alpha-3B by using the following code snippet:

from transformers import AutoModelForCausalLM, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("stabilityai/stablecode-instruct-alpha-3b")
model = AutoModelForCausalLM.from_pretrained(
  "stabilityai/stablecode-instruct-alpha-3b",
  trust_remote_code=True,
  torch_dtype="auto",
)
model.cuda()
inputs = tokenizer("###Instruction\nGenerate a python function to find number of CPU cores###Response\n", return_tensors="pt").to("cuda")
tokens = model.generate(
  **inputs,
  max_new_tokens=48,
  temperature=0.2,
  do_sample=True,
)
print(tokenizer.decode(tokens[0], skip_special_tokens=True))

Model Details

  • Developed by: Stability AI
  • Model type: StableCode-Instruct-Alpha-3B models are auto-regressive language models based on the transformer decoder architecture.
  • Language(s): Code
  • Library: GPT-NeoX
  • License : Model checkpoints are licensed under the StableCode Research License Copyright (c) Stability AI Ltd. All Rights Reserved
  • Contact: For questions and comments about the model, please email [email protected]

Model Architecture

Parameters Hidden Size Layers Heads Sequence Length
2,796,431,360 2560 32 32 4096
  • Decoder Layer: Parallel Attention and MLP residuals with a single input LayerNorm (Wang & Komatsuzaki, 2021)
  • Position Embeddings: Rotary Position Embeddings (Su et al., 2021)
  • Bias: LayerNorm bias terms only

Training

StableCode-Instruct-Alpha-3B is the instruction finetuned version on StableCode-Completion-Alpha-3B with code instruction datasets.

Use and Limitations

Intended Use

StableCode-Instruct-Alpha-3B independently generates new code completions, but we recommend that you use StableCode-Instruct-Alpha-3B together with the tool developed by BigCode and HuggingFace (huggingface/huggingface-vscode: Code completion VSCode extension for OSS models (github.com)), to identify and, if necessary, attribute any outputs that match training code.

Limitations and bias

This model is intended to be used responsibly. It is not intended to be used to create unlawful content of any kind, to further any unlawful activity, or to engage in activities with a high risk of physical or economic harm.

How to cite 

@misc{StableCodeInstructAlpha, 
      url={[https://huggingface.co./stabilityai/stablecode-instruct-alpha-3b](https://huggingface.co./stabilityai/stablecode-instruct-alpha-3b)}, 
      title={Stable Code Instruct Alpha}, 
      author={Adithyan, Reshinth and Phung, Duy and Cooper, Nathan and Pinnaparaju, Nikhil and Laforte, Christian}
}