Text Classification
Transformers
Safetensors
English
multilingual
xlm-roberta
multi-label-classification
multi-head-classification
disaster-response
humanitarian-aid
social-media
twitter
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use spencercdz/xlm-roberta-sentiment-requests with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spencercdz/xlm-roberta-sentiment-requests with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="spencercdz/xlm-roberta-sentiment-requests")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("spencercdz/xlm-roberta-sentiment-requests") model = AutoModel.from_pretrained("spencercdz/xlm-roberta-sentiment-requests", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from spencercdz/xlm-roberta-sentiment-requests: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/spencercdz/xlm-roberta-sentiment-requests/resolve/f6e2dfcd3beffd5f2b51af61fe8b98775d3a0989/tokenizer.json
- Command line
-
hf download hf://spencercdz/xlm-roberta-sentiment-requests@f6e2dfcd3beffd5f2b51af61fe8b98775d3a0989/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/spencercdz/xlm-roberta-sentiment-requests/resolve/f6e2dfcd3beffd5f2b51af61fe8b98775d3a0989/tokenizer.json
17.1 MB
- Xet hash:
- aa0224afe11fc37ae6beecfd10a7c1b862ed1d96259a799c6488e7da78f9ec53
- Size of remote file:
- 17.1 MB
- SHA256:
- 61933031e2e4f42c3c1cb58e86d83618d05e1c22bd10c2d2a01efd33ba241989
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.