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-3Bmodels 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
lm@stability.ai
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}
}