bigcode / starcoderbase-1b

huggingface.co
Total runs: 8.8K
24-hour runs: 0
7-day runs: 594
30-day runs: 4.7K
Model's Last Updated: September 14 2023
text-generation

Introduction of starcoderbase-1b

Model Details of starcoderbase-1b

StarCoderBase-1B

1B version of StarCoderBase .

Table of Contents
  1. Model Summary
  2. Use
  3. Limitations
  4. Training
  5. License
  6. Citation
Model Summary

StarCoderBase-1B is a 1B parameter model trained on 80+ programming languages from The Stack (v1.2) , with opt-out requests excluded. The model uses Multi Query Attention , a context window of 8192 tokens , and was trained using the Fill-in-the-Middle objective on 1 trillion tokens.

Use
Intended use

The model was trained on GitHub code. As such it is not an instruction model and commands like "Write a function that computes the square root." do not work well. However, by using the Tech Assistant prompt you can turn it into a capable technical assistant.

Feel free to share your generations in the Community tab!

Generation
# pip install -q transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

checkpoint = "bigcode/starcoderbase-1b"
device = "cuda" # for GPU usage or "cpu" for CPU usage

tokenizer = AutoTokenizer.from_pretrained(checkpoint)
model = AutoModelForCausalLM.from_pretrained(checkpoint).to(device)

inputs = tokenizer.encode("def print_hello_world():", return_tensors="pt").to(device)
outputs = model.generate(inputs)
print(tokenizer.decode(outputs[0]))
Fill-in-the-middle

Fill-in-the-middle uses special tokens to identify the prefix/middle/suffix part of the input and output:

input_text = "<fim_prefix>def print_hello_world():\n    <fim_suffix>\n    print('Hello world!')<fim_middle>"
inputs = tokenizer.encode(input_text, return_tensors="pt").to(device)
outputs = model.generate(inputs)
print(tokenizer.decode(outputs[0]))
Attribution & Other Requirements

The pretraining dataset of the model was filtered for permissive licenses only. Nevertheless, the model can generate source code verbatim from the dataset. The code's license might require attribution and/or other specific requirements that must be respected. We provide a search index that let's you search through the pretraining data to identify where generated code came from and apply the proper attribution to your code.

Limitations

The model has been trained on source code from 80+ programming languages. The predominant natural language in source code is English although other languages are also present. As such the model is capable of generating code snippets provided some context but the generated code is not guaranteed to work as intended. It can be inefficient, contain bugs or exploits. See the paper for an in-depth discussion of the model limitations.

Training

Model
  • Architecture: GPT-2 model with multi-query attention and Fill-in-the-Middle objective
  • Pretraining steps: 500k
  • Pretraining tokens: 1 trillion
  • Precision: bfloat16
Hardware
  • GPUs: 128 Tesla A100
  • Training time: 11 days
Software

License

The model is licensed under the BigCode OpenRAIL-M v1 license agreement. You can find the full agreement here .

Citation

@article{li2023starcoder,
      title={StarCoder: may the source be with you!}, 
      author={Raymond Li and Loubna Ben Allal and Yangtian Zi and Niklas Muennighoff and Denis Kocetkov and Chenghao Mou and Marc Marone and Christopher Akiki and Jia Li and Jenny Chim and Qian Liu and Evgenii Zheltonozhskii and Terry Yue Zhuo and Thomas Wang and Olivier Dehaene and Mishig Davaadorj and Joel Lamy-Poirier and João Monteiro and Oleh Shliazhko and Nicolas Gontier and Nicholas Meade and Armel Zebaze and Ming-Ho Yee and Logesh Kumar Umapathi and Jian Zhu and Benjamin Lipkin and Muhtasham Oblokulov and Zhiruo Wang and Rudra Murthy and Jason Stillerman and Siva Sankalp Patel and Dmitry Abulkhanov and Marco Zocca and Manan Dey and Zhihan Zhang and Nour Fahmy and Urvashi Bhattacharyya and Wenhao Yu and Swayam Singh and Sasha Luccioni and Paulo Villegas and Maxim Kunakov and Fedor Zhdanov and Manuel Romero and Tony Lee and Nadav Timor and Jennifer Ding and Claire Schlesinger and Hailey Schoelkopf and Jan Ebert and Tri Dao and Mayank Mishra and Alex Gu and Jennifer Robinson and Carolyn Jane Anderson and Brendan Dolan-Gavitt and Danish Contractor and Siva Reddy and Daniel Fried and Dzmitry Bahdanau and Yacine Jernite and Carlos Muñoz Ferrandis and Sean Hughes and Thomas Wolf and Arjun Guha and Leandro von Werra and Harm de Vries},
      year={2023},
      eprint={2305.06161},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Runs of bigcode starcoderbase-1b on huggingface.co

8.8K
Total runs
0
24-hour runs
578
3-day runs
594
7-day runs
4.7K
30-day runs

More Information About starcoderbase-1b huggingface.co Model

More starcoderbase-1b license Visit here:

https://choosealicense.com/licenses/bigcode-openrail-m

starcoderbase-1b huggingface.co

starcoderbase-1b huggingface.co is an AI model on huggingface.co that provides starcoderbase-1b's model effect (), which can be used instantly with this bigcode starcoderbase-1b model. huggingface.co supports a free trial of the starcoderbase-1b model, and also provides paid use of the starcoderbase-1b. Support call starcoderbase-1b model through api, including Node.js, Python, http.

starcoderbase-1b huggingface.co Url

https://huggingface.co/bigcode/starcoderbase-1b

bigcode starcoderbase-1b online free

starcoderbase-1b huggingface.co is an online trial and call api platform, which integrates starcoderbase-1b's modeling effects, including api services, and provides a free online trial of starcoderbase-1b, you can try starcoderbase-1b online for free by clicking the link below.

bigcode starcoderbase-1b online free url in huggingface.co:

https://huggingface.co/bigcode/starcoderbase-1b

starcoderbase-1b install

starcoderbase-1b is an open source model from GitHub that offers a free installation service, and any user can find starcoderbase-1b on GitHub to install. At the same time, huggingface.co provides the effect of starcoderbase-1b install, users can directly use starcoderbase-1b installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

starcoderbase-1b install url in huggingface.co:

https://huggingface.co/bigcode/starcoderbase-1b

Url of starcoderbase-1b

starcoderbase-1b huggingface.co Url

Provider of starcoderbase-1b huggingface.co

bigcode
ORGANIZATIONS

Other API from bigcode

huggingface.co

Total runs: 1.1M
Run Growth: 717.0K
Growth Rate: 68.17%
Updated: March 04 2024
huggingface.co

Total runs: 35.3K
Run Growth: 26.7K
Growth Rate: 78.08%
Updated: June 11 2024
huggingface.co

Total runs: 18.6K
Run Growth: 1.0K
Growth Rate: 5.67%
Updated: October 08 2024
huggingface.co

Total runs: 7.0K
Run Growth: -48.3K
Growth Rate: -719.62%
Updated: October 12 2023
huggingface.co

Total runs: 2.1K
Run Growth: -472
Growth Rate: -23.95%
Updated: May 10 2023
huggingface.co

Total runs: 1.6K
Run Growth: -1.9K
Growth Rate: -128.21%
Updated: May 11 2023
huggingface.co

Total runs: 376
Run Growth: -287
Growth Rate: -101.06%
Updated: July 24 2023
huggingface.co

Total runs: 286
Run Growth: 93
Growth Rate: 32.52%
Updated: August 17 2023
huggingface.co

Total runs: 159
Run Growth: -16
Growth Rate: -10.06%
Updated: August 17 2023
huggingface.co

Total runs: 25
Run Growth: -145
Growth Rate: -580.00%
Updated: August 13 2023
huggingface.co

Total runs: 19
Run Growth: 15
Growth Rate: 78.95%
Updated: January 01 2024
huggingface.co

Total runs: 18
Run Growth: 1
Growth Rate: 5.56%
Updated: August 05 2023
huggingface.co

Total runs: 0
Run Growth: 0
Growth Rate: 0.00%
Updated: February 28 2024
huggingface.co

Total runs: 0
Run Growth: 0
Growth Rate: 0.00%
Updated: January 14 2025