Instructions to use Alireza1044/albert-base-v2-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alireza1044/albert-base-v2-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Alireza1044/albert-base-v2-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Alireza1044/albert-base-v2-mrpc") model = AutoModelForSequenceClassification.from_pretrained("Alireza1044/albert-base-v2-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Alireza1044/albert-base-v2-mrpc: direct link, hf CLI and curl.
- Browser
- Download file 46.8 MB
-
https://huggingface.co/Alireza1044/albert-base-v2-mrpc/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Alireza1044/albert-base-v2-mrpc/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Alireza1044/albert-base-v2-mrpc/resolve/main/pytorch_model.bin
46.8 MB
- Xet hash:
- 4a923d8a4a3bdcb598be407be129158242493650b4ef28f65961b2373595e235
- Size of remote file:
- 46.8 MB
- SHA256:
- cd6c004c9dadcfe3c11463044cd796f040aa658d1270a6112c6e7591a4ee9701
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