Instructions to use HiTZ/A2T_RoBERTa_SMFA_WikiEvents-arg_ACE-arg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiTZ/A2T_RoBERTa_SMFA_WikiEvents-arg_ACE-arg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="HiTZ/A2T_RoBERTa_SMFA_WikiEvents-arg_ACE-arg")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HiTZ/A2T_RoBERTa_SMFA_WikiEvents-arg_ACE-arg") model = AutoModelForSequenceClassification.from_pretrained("HiTZ/A2T_RoBERTa_SMFA_WikiEvents-arg_ACE-arg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from HiTZ/A2T_RoBERTa_SMFA_WikiEvents-arg_ACE-arg: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/HiTZ/A2T_RoBERTa_SMFA_WikiEvents-arg_ACE-arg/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://HiTZ/A2T_RoBERTa_SMFA_WikiEvents-arg_ACE-arg/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HiTZ/A2T_RoBERTa_SMFA_WikiEvents-arg_ACE-arg/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 70048a0d9cf13f2bfab47e3fb98dbf31352e699eae60b1a85a28e409fc70e550
- Size of remote file:
- 1.42 GB
- SHA256:
- c3ae6b82e5015fbe286f6e696940e39a391e667df242c6d48cde79a61ecb0681
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