Instructions to use tals/albert-base-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tals/albert-base-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tals/albert-base-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tals/albert-base-mnli") model = AutoModelForSequenceClassification.from_pretrained("tals/albert-base-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61020d1cb85a0debf42665ad6f3b937ff71ec12f0c34236e449700fa6db06788
- Size of remote file:
- 46.8 MB
- SHA256:
- fc616b5037f0753aaf648408ce916db85458912927ff9401b6b0593be82f25ef
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