Instructions to use VMware/vinilm-2021-qa-evaluator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VMware/vinilm-2021-qa-evaluator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VMware/vinilm-2021-qa-evaluator")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VMware/vinilm-2021-qa-evaluator") model = AutoModelForSequenceClassification.from_pretrained("VMware/vinilm-2021-qa-evaluator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from VMware/vinilm-2021-qa-evaluator: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/VMware/vinilm-2021-qa-evaluator/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://VMware/vinilm-2021-qa-evaluator@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/VMware/vinilm-2021-qa-evaluator/resolve/refs%2Fpr%2F1/pytorch_model.bin
268 MB
- Xet hash:
- 214fcf4307fbb81b7415a1bdbcea120d36a1af80fb6f102d060d73da6f622af4
- Size of remote file:
- 268 MB
- SHA256:
- 28edf2f00cd7dd372e3311b1952110e3641ea391d86d7ce2a72d7ba5e5d98016
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