Instructions to use WilliamWen/extract_features with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WilliamWen/extract_features with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="WilliamWen/extract_features")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("WilliamWen/extract_features") model = AutoModelForTokenClassification.from_pretrained("WilliamWen/extract_features") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
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:dea209e1ae8ea0bf4b9710ca87cf39086a75eb7b68d724e33085e0c32149c388
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size 430952388
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