Instructions to use ahnaf702/SentibertLarge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahnaf702/SentibertLarge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ahnaf702/SentibertLarge")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ahnaf702/SentibertLarge") model = AutoModelForSequenceClassification.from_pretrained("ahnaf702/SentibertLarge", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ahnaf702/SentibertLarge: direct link, hf CLI and curl.
- Browser
- Download file 1.03 MB
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https://huggingface.co/ahnaf702/SentibertLarge/resolve/df236e4ec9c9fb332138cda4a5eebfbccfde29fd/tokenizer.json
- Command line
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hf download hf://ahnaf702/SentibertLarge@df236e4ec9c9fb332138cda4a5eebfbccfde29fd/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/ahnaf702/SentibertLarge/resolve/df236e4ec9c9fb332138cda4a5eebfbccfde29fd/tokenizer.json
1.03 MB
File too large to display, you can check the raw version instead.