Instructions to use rpii2023/Je_baat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rpii2023/Je_baat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rpii2023/Je_baat")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("rpii2023/Je_baat") model = AutoModelForTokenClassification.from_pretrained("rpii2023/Je_baat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from rpii2023/Je_baat: direct link, hf CLI and curl.
- Browser
- Download file 1.46 MB
-
https://huggingface.co/rpii2023/Je_baat/resolve/main/tokenizer.json
- Command line
-
hf download hf://rpii2023/Je_baat/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/rpii2023/Je_baat/resolve/main/tokenizer.json
1.46 MB
File too large to display, you can check the raw version instead.