Instructions to use boltuix/bert-lite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boltuix/bert-lite with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boltuix/bert-lite")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("boltuix/bert-lite") model = AutoModelForMaskedLM.from_pretrained("boltuix/bert-lite") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
This is an automated PR created with https://huggingface.co/spaces/safetensors/convert
This new file is equivalent to pytorch_model.bin but safe in the sense that
no arbitrary code can be put into it.
These files also happen to load much faster than their pytorch counterpart:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb
The widgets on your model page will run using this model even if this is not merged
making sure the file actually works.
If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions
Feel free to ignore this PR.
Thanks for the automated safetensors PR!
We've already added the .safetensors version and closed this PR accordingly.
Everything is working fine on our side.
Appreciate the effort and the performance/safety boost π