Instructions to use akumar33/ManuBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akumar33/ManuBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="akumar33/ManuBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("akumar33/ManuBERT") model = AutoModelForMaskedLM.from_pretrained("akumar33/ManuBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
Verified signatureThis 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.1f6c6ce
-
Upload tokenizer_config.json
96c0397 -
Upload tokenizer.json
ec9044d -
Delete tokenizer_config.json
2ba8248 -
Delete tokenizer.json
f18964c -
Update config.json
91b9718 -
Delete vocab.txt
77ad611
-
Upload vocab.txt
ed02693 -
Upload tokenizer_config.json
8acc74d -
Upload tokenizer.json
0f28875 -
Upload special_tokens_map.json
da227f1 -
Upload pytorch_model.bin with git-lfs
ccc4ec0 -
Upload config.json
1c53bfc -
initial commit
24de43f