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:
- 9e5f681f6dbe26603c274cd25e8c0c181130d8b67a6d57094d0983526ab66b56
- Size of remote file:
- 266 MB
- SHA256:
- f50558c54ec6adfd38c3613e4fff378b72357006b34aeaed434537bf73207aff
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