Instructions to use prajjwal1/albert-base-v2-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prajjwal1/albert-base-v2-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="prajjwal1/albert-base-v2-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("prajjwal1/albert-base-v2-mnli") model = AutoModelForSequenceClassification.from_pretrained("prajjwal1/albert-base-v2-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from prajjwal1/albert-base-v2-mnli: direct link, hf CLI and curl.
- Browser
- Download file 760 kB
-
https://huggingface.co/prajjwal1/albert-base-v2-mnli/resolve/7faee6ffbbbaf5e61bc357ec4ba9545654ec1fe9/spiece.model
- Command line
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hf download hf://prajjwal1/albert-base-v2-mnli@7faee6ffbbbaf5e61bc357ec4ba9545654ec1fe9/spiece.model
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curl -L -o spiece.model https://huggingface.co/prajjwal1/albert-base-v2-mnli/resolve/7faee6ffbbbaf5e61bc357ec4ba9545654ec1fe9/spiece.model
760 kB
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