Instructions to use textattack/albert-base-v2-QQP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/albert-base-v2-QQP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/albert-base-v2-QQP")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/albert-base-v2-QQP") model = AutoModelForSequenceClassification.from_pretrained("textattack/albert-base-v2-QQP", 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.96db8de
-
Update special_tokens_map.json
8f4e247 -
Update train_args.json
e1238f5 -
Update config.json
1a12aad -
Update log.txt
d8a2d6f -
Update spiece.model
d6a1c79 -
Update pytorch_model.bin
da2d9ca -
Update README.md
aeebae3 -
Update tokenizer_config.json
3ee745b -
initial commit
2434fba