Instructions to use hf-internal-testing/tiny-random-MT5ForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MT5ForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MT5ForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MT5ForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MT5ForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-MT5ForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-MT5ForSequenceClassification/resolve/refs%2Fpr%2F67/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-MT5ForSequenceClassification@refs/pr/67/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-MT5ForSequenceClassification/resolve/refs%2Fpr%2F67/model.safetensors
32.2 MB
- Xet hash:
- 4b26f26a9548c99a9c22f8f9685d82c25c66144a52c01c490fc731e2e15afb3d
- Size of remote file:
- 32.2 MB
- SHA256:
- a2917cb8d1d9121e3b59a36a46e9311521bd0f4c09eb62a161fd0e68fd7d49ba
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