Instructions to use henryscheible/mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/mnli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/mnli") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from henryscheible/mnli: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/henryscheible/mnli/resolve/main/training_args.bin
- Command line
-
hf download hf://henryscheible/mnli/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/henryscheible/mnli/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- 2e0a77b2107d0bf892d716ab412086356b0819e36daa04b4da194e6a125fba53
- Size of remote file:
- 3.38 kB
- SHA256:
- 099a57fae2b41cfe9859c7be81fe1c6ba659b79301541803f560193721668cc7
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