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 spiece.model from hf-internal-testing/tiny-random-MT5ForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 4.31 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-MT5ForSequenceClassification/resolve/refs%2Fpr%2F2/spiece.model
- Command line
-
hf download hf://hf-internal-testing/tiny-random-MT5ForSequenceClassification@refs/pr/2/spiece.model
-
curl -L -o spiece.model https://huggingface.co/hf-internal-testing/tiny-random-MT5ForSequenceClassification/resolve/refs%2Fpr%2F2/spiece.model
4.31 MB
- Xet hash:
- c002d43daac2cff8ed238836274d14498980e85c24cfd4076159b27131e91e77
- Size of remote file:
- 4.31 MB
- SHA256:
- ef78f86560d809067d12bac6c09f19a462cb3af3f54d2b8acbba26e1433125d6
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