Instructions to use hf-internal-testing/tiny-random-UMT5ForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UMT5ForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-UMT5ForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-UMT5ForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-UMT5ForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from hf-internal-testing/tiny-random-UMT5ForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 16.8 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-UMT5ForSequenceClassification/resolve/da7a89fd44891712ddcfa5608c68de983ac8c1c2/tokenizer.json
- Command line
-
hf download hf://hf-internal-testing/tiny-random-UMT5ForSequenceClassification@da7a89fd44891712ddcfa5608c68de983ac8c1c2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/hf-internal-testing/tiny-random-UMT5ForSequenceClassification/resolve/da7a89fd44891712ddcfa5608c68de983ac8c1c2/tokenizer.json
16.8 MB
- Xet hash:
- 9ec432bdbf359181405fdcad8c81eb9d73703a3530ab6b9f1a6972244189d435
- Size of remote file:
- 16.8 MB
- SHA256:
- 8c423d8500263e0f8098ca1174fea42064b7b82a87ef4f757c75aab4c8310186
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.