Instructions to use Valencio/LLM_course_MLM_model_TokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Valencio/LLM_course_MLM_model_TokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Valencio/LLM_course_MLM_model_TokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Valencio/LLM_course_MLM_model_TokenClassification") model = AutoModelForTokenClassification.from_pretrained("Valencio/LLM_course_MLM_model_TokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a44326cfee702fc79a0ce3ff7b90a6fd95cf5aaf29d56c9c92e29550eb1f80b
- Size of remote file:
- 5.2 kB
- SHA256:
- adaa12d3c83db290a3cc432abbfa68426031b83343bc3a2bf2b550c2db00bf4f
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