Instructions to use eawang/bart_num_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eawang/bart_num_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eawang/bart_num_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eawang/bart_num_model") model = AutoModelForSequenceClassification.from_pretrained("eawang/bart_num_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from eawang/bart_num_model: direct link, hf CLI and curl.
- Browser
- Download file 560 MB
-
https://huggingface.co/eawang/bart_num_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://eawang/bart_num_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/eawang/bart_num_model/resolve/main/pytorch_model.bin
560 MB
- Xet hash:
- 9ccdd80312c2a96068b541dfa648e6e2ae7f34627c53fd9c33392aeab9acd3fb
- Size of remote file:
- 560 MB
- SHA256:
- 27dc3e28e74d17ec56f01ea2a378392f78ea1424f8583de4eeafa7840f0e9d5b
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