Instructions to use bertin-project/bertin-base-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bertin-project/bertin-base-random with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bertin-project/bertin-base-random")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bertin-project/bertin-base-random") model = AutoModelForMaskedLM.from_pretrained("bertin-project/bertin-base-random", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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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.d7efed6
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Automatic correction of README.md metadata. Contact website@huggingface.co for any question
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Step... (230001/250000 | Loss: 1.7595738172531128, Acc: 0.6519749760627747): 92%|███████████████████▎ | 230248/250000 [111:01:26<10:03:20, 1.83s/it]
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Step... (220001/250000 | Loss: 1.7591936588287354, Acc: 0.6520245671272278): 88%|██████████████████▌ | 220518/250000 [106:16:53<14:56:57, 1.83s/it]
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Model at 210k steps, mlm acc 0.6509
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