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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a5b0f0b5ff7f3c563f9497758351a0b2b17c92e700efe2577c9653ddf657ac7
- Size of remote file:
- 3.52 kB
- SHA256:
- eb7a9b82ae236ecca5b3159075078531b14e7511b39efe729d12af20718bbc46
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