Instructions to use Jsevisal/ft-bert-large-gest-pred-seqeval-partialmatch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jsevisal/ft-bert-large-gest-pred-seqeval-partialmatch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Jsevisal/ft-bert-large-gest-pred-seqeval-partialmatch")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Jsevisal/ft-bert-large-gest-pred-seqeval-partialmatch") model = AutoModelForTokenClassification.from_pretrained("Jsevisal/ft-bert-large-gest-pred-seqeval-partialmatch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitignore from Jsevisal/ft-bert-large-gest-pred-seqeval-partialmatch: direct link, hf CLI and curl.
- Browser
- Download file 13 Bytes
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https://huggingface.co/Jsevisal/ft-bert-large-gest-pred-seqeval-partialmatch/resolve/main/.gitignore
- Command line
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hf download hf://Jsevisal/ft-bert-large-gest-pred-seqeval-partialmatch/.gitignore
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curl -L -o .gitignore https://huggingface.co/Jsevisal/ft-bert-large-gest-pred-seqeval-partialmatch/resolve/main/.gitignore
13 Bytes
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