Instructions to use PaulAdversarial/PAN_twitter_hate_speech_2021_ES_MT5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PaulAdversarial/PAN_twitter_hate_speech_2021_ES_MT5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PaulAdversarial/PAN_twitter_hate_speech_2021_ES_MT5") model = AutoModelForSeq2SeqLM.from_pretrained("PaulAdversarial/PAN_twitter_hate_speech_2021_ES_MT5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from PaulAdversarial/PAN_twitter_hate_speech_2021_ES_MT5: direct link, hf CLI and curl.
- Browser
- Download file 1.2 GB
-
https://huggingface.co/PaulAdversarial/PAN_twitter_hate_speech_2021_ES_MT5/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://PaulAdversarial/PAN_twitter_hate_speech_2021_ES_MT5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/PaulAdversarial/PAN_twitter_hate_speech_2021_ES_MT5/resolve/main/pytorch_model.bin
1.2 GB
- Xet hash:
- dba7f5965fe14f5b21d97e57a96ddb1db1caaa0fd7645d46e6dd86218c811a63
- Size of remote file:
- 1.2 GB
- SHA256:
- 53f4f6d7b2355e2bfcbde18af7b571f48495aef0ea62c0963200fc42c864b750
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.