Instructions to use Colby/starcoderbase-7b-coding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Colby/starcoderbase-7b-coding with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Colby/starcoderbase-7b-coding", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| base_model: bigcode/starcoderbase-7b | |
| library_name: transformers | |
| model_name: starcoderbase-7b-coding | |
| tags: | |
| - generated_from_trainer | |
| - sft | |
| - hf_jobs | |
| - trl | |
| licence: license | |
| # Model Card for starcoderbase-7b-coding | |
| This model is a fine-tuned version of [bigcode/starcoderbase-7b](https://huggingface.co/bigcode/starcoderbase-7b). | |
| It has been trained using [TRL](https://github.com/huggingface/trl). | |
| ## Quick start | |
| ```python | |
| from transformers import pipeline | |
| question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" | |
| generator = pipeline("text-generation", model="Colby/starcoderbase-7b-coding", device="cuda") | |
| output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] | |
| print(output["generated_text"]) | |
| ``` | |
| ## Training procedure | |
| This model was trained with SFT. | |
| ### Framework versions | |
| - TRL: 1.4.0 | |
| - Transformers: 5.8.0 | |
| - Pytorch: 2.11.0 | |
| - Datasets: 4.8.5 | |
| - Tokenizers: 0.22.2 | |
| ## Citations | |
| Cite TRL as: | |
| ```bibtex | |
| @software{vonwerra2020trl, | |
| title = {{TRL: Transformers Reinforcement Learning}}, | |
| author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin}, | |
| license = {Apache-2.0}, | |
| url = {https://github.com/huggingface/trl}, | |
| year = {2020} | |
| } | |
| ``` |