Instructions to use anirudh21/albert-large-v2-finetuned-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anirudh21/albert-large-v2-finetuned-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anirudh21/albert-large-v2-finetuned-mnli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anirudh21/albert-large-v2-finetuned-mnli") model = AutoModelForSequenceClassification.from_pretrained("anirudh21/albert-large-v2-finetuned-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from anirudh21/albert-large-v2-finetuned-mnli: direct link, hf CLI and curl.
- Browser
- Download file 70.8 MB
-
https://huggingface.co/anirudh21/albert-large-v2-finetuned-mnli/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://anirudh21/albert-large-v2-finetuned-mnli/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/anirudh21/albert-large-v2-finetuned-mnli/resolve/main/pytorch_model.bin
70.8 MB
- Xet hash:
- 3157144cc4f3dcec5d2a47a1b995785df3814fb3b42aa2e6b9f0d35b2c014dbd
- Size of remote file:
- 70.8 MB
- SHA256:
- 8176a3bc66863cfde89202857c3122a27c5b91faba965efe169f616f821055ea
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