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/45b7feff89d18a7768ee092c1367545e6e6b03ef/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-MT5ForSequenceClassification@45b7feff89d18a7768ee092c1367545e6e6b03ef/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-MT5ForSequenceClassification/resolve/45b7feff89d18a7768ee092c1367545e6e6b03ef/model.safetensors
32.2 MB
- Xet hash:
- 232acdfea442d94719798e72618f6b3ad95b69542f5a8e49f70ceb60396f48a6
- Size of remote file:
- 32.2 MB
- SHA256:
- adff6e69ce03c614f494df5d2fff2e8ba7cd8ea90ff7bba36a741c0eb1602743
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