Instructions to use Bayesian-KD/SmolLM-14m-Dolma-v0.1-Proposed-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bayesian-KD/SmolLM-14m-Dolma-v0.1-Proposed-full with Transformers:
# Load model directly from transformers import AutoTokenizer, OutputEmbeddingSelectiveUpdate tokenizer = AutoTokenizer.from_pretrained("Bayesian-KD/SmolLM-14m-Dolma-v0.1-Proposed-full") model = OutputEmbeddingSelectiveUpdate.from_pretrained("Bayesian-KD/SmolLM-14m-Dolma-v0.1-Proposed-full") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2cbbf9cf1b66369d23f73ec340bb2920e171d08f3a48b61dbbd8fa884ec199f6
- Size of remote file:
- 6.71 kB
- SHA256:
- e04f55df0894a8b2d1cdfafd9cb6660d0126fc9087afdd725fe71927d9c2c163
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.