Instructions to use UTibetNLP/tibetan-bert_tusa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UTibetNLP/tibetan-bert_tusa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="UTibetNLP/tibetan-bert_tusa")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("UTibetNLP/tibetan-bert_tusa") model = AutoModelForSequenceClassification.from_pretrained("UTibetNLP/tibetan-bert_tusa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:80de76ed24d48c689ba92333ebfaa3856a4359638ac5babc8e0e963f7376e8b2
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size 443319296
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