Instructions to use KPROCKS/Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KPROCKS/Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KPROCKS/Model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KPROCKS/Model") model = AutoModelForSequenceClassification.from_pretrained("KPROCKS/Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from KPROCKS/Model: direct link, hf CLI and curl.
- Browser
- Download file 102 Bytes
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https://huggingface.co/KPROCKS/Model/resolve/main/README.md
- Command line
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hf download hf://KPROCKS/Model/README.md
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curl -L -o README.md https://huggingface.co/KPROCKS/Model/resolve/main/README.md
102 Bytes
metadata
license: mit
language:
- gu
base_model:
- l3cube-pune/gujarati-bert
library_name: transformers