Instructions to use Cheng98/opt-125m-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cheng98/opt-125m-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cheng98/opt-125m-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cheng98/opt-125m-mnli") model = AutoModelForSequenceClassification.from_pretrained("Cheng98/opt-125m-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c042a5b2643037cb7d7131051f4e1443145117d00e58eb0dac056735e324da8
- Size of remote file:
- 501 MB
- SHA256:
- 48e2d85c9a1c190056db24345872a70d4ba562f6fcbf9d928de15808a28c1a07
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