Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use JiaJiaCen/xlm-roberta-base-language-detection-disaster-twitter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JiaJiaCen/xlm-roberta-base-language-detection-disaster-twitter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JiaJiaCen/xlm-roberta-base-language-detection-disaster-twitter")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JiaJiaCen/xlm-roberta-base-language-detection-disaster-twitter") model = AutoModelForSequenceClassification.from_pretrained("JiaJiaCen/xlm-roberta-base-language-detection-disaster-twitter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from JiaJiaCen/xlm-roberta-base-language-detection-disaster-twitter: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/JiaJiaCen/xlm-roberta-base-language-detection-disaster-twitter/resolve/af47d5380d71b1bdf48c2ae35a9f6462a6123a9e/model.safetensors
- Command line
-
hf download hf://JiaJiaCen/xlm-roberta-base-language-detection-disaster-twitter@af47d5380d71b1bdf48c2ae35a9f6462a6123a9e/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/JiaJiaCen/xlm-roberta-base-language-detection-disaster-twitter/resolve/af47d5380d71b1bdf48c2ae35a9f6462a6123a9e/model.safetensors
1.11 GB
- Xet hash:
- 385af74f7ed6c5758a8508e2edf2bb8c501dc6312fd07cad27b7f056fcb47ccc
- Size of remote file:
- 1.11 GB
- SHA256:
- 6a1e791f6afba86f9e1486003c50399069db89583afb3ab3c90e233e79697197
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