Instructions to use reyvan/bert_large_TruthfulAndSumm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reyvan/bert_large_TruthfulAndSumm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="reyvan/bert_large_TruthfulAndSumm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("reyvan/bert_large_TruthfulAndSumm") model = AutoModelForSequenceClassification.from_pretrained("reyvan/bert_large_TruthfulAndSumm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from reyvan/bert_large_TruthfulAndSumm: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/reyvan/bert_large_TruthfulAndSumm/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://reyvan/bert_large_TruthfulAndSumm/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/reyvan/bert_large_TruthfulAndSumm/resolve/main/pytorch_model.bin
1.34 GB
- Xet hash:
- 6b2dc65b5d4fd6c3c3c3812f45311557fec714db67beea3387a1ecbc66247a00
- Size of remote file:
- 1.34 GB
- SHA256:
- e6733c19b1b1ef80a55ede10d08006a155f03e5825cccf78ffa0154084b251a4
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