Instructions to use Twitter/twhin-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Twitter/twhin-bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Twitter/twhin-bert-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Twitter/twhin-bert-base") model = AutoModelForMaskedLM.from_pretrained("Twitter/twhin-bert-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Twitter/twhin-bert-base: direct link, hf CLI and curl.
- Browser
- Download file 1.12 GB
-
https://huggingface.co/Twitter/twhin-bert-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Twitter/twhin-bert-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Twitter/twhin-bert-base/resolve/main/pytorch_model.bin
1.12 GB
- Xet hash:
- 7f6fbcb67d727f71a550f87d7fef37298d6332bd664304ba457e7d30fa70af75
- Size of remote file:
- 1.12 GB
- SHA256:
- 2726745fb5a67940462d1ed229a007ef49abcc074be4e829325c67912172f46b
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