Instructions to use hf-internal-testing/tiny-random-XmodForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XmodForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-XmodForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XmodForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-XmodForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-XmodForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 32.3 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-XmodForSequenceClassification/resolve/c84ccc5de0c72e8bcc4712113e62ff7bc14082c9/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-XmodForSequenceClassification@c84ccc5de0c72e8bcc4712113e62ff7bc14082c9/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-XmodForSequenceClassification/resolve/c84ccc5de0c72e8bcc4712113e62ff7bc14082c9/pytorch_model.bin
32.3 MB
- Xet hash:
- e111e48fba234d397a5cf71bb9e302c98255a4f990d788c89406a88b3672d7ec
- Size of remote file:
- 32.3 MB
- SHA256:
- d06ad61b0840018741b8f59b53e7b9507ad3c8ed3edd5f168d6daaeb5da44cf3
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