Instructions to use textattack/albert-base-v2-snli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/albert-base-v2-snli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/albert-base-v2-snli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/albert-base-v2-snli") model = AutoModelForSequenceClassification.from_pretrained("textattack/albert-base-v2-snli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
This is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.ece9f71
-
Update config.json
706e88d -
Update pytorch_model.bin
281b196 -
Update special_tokens_map.json
6d25eb6 -
Update spiece.model
ffc83e7 -
Update tokenizer_config.json
0580433 -
Update README.md
67a1581 -
Update log.txt
d008899 -
Update train_args.json
12ed9e0 -
initial commit
fd39b13