Instructions to use Cheng98/opt-350m-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cheng98/opt-350m-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cheng98/opt-350m-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cheng98/opt-350m-mnli") model = AutoModelForSequenceClassification.from_pretrained("Cheng98/opt-350m-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Cheng98/opt-350m-mnli: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/Cheng98/opt-350m-mnli/resolve/main/training_args.bin
- Command line
-
hf download hf://Cheng98/opt-350m-mnli/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Cheng98/opt-350m-mnli/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- eac67447b042db01163aeb5cc401b9ae2e63888f558beee8e6fdd866c804966e
- Size of remote file:
- 3.96 kB
- SHA256:
- 92d5242ba25e0f5c5478fd83a418c1b9b6698b5ec287e3c143a09a48a4f8b8f9
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