Instructions to use sugamjais/xtreme-er with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sugamjais/xtreme-er with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sugamjais/xtreme-er")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sugamjais/xtreme-er") model = AutoModelForSequenceClassification.from_pretrained("sugamjais/xtreme-er", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download valid.csv from sugamjais/xtreme-er: direct link, hf CLI and curl.
- Browser
- Download file 685 kB
-
https://huggingface.co/sugamjais/xtreme-er/resolve/main/valid.csv
- Command line
-
hf download hf://sugamjais/xtreme-er/valid.csv
-
curl -L -o valid.csv https://huggingface.co/sugamjais/xtreme-er/resolve/main/valid.csv
685 kB
File too large to display, you can check the raw version instead.