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")# 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") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#6 opened about 2 years ago
by
SFconvertbot
Update tiny models for UMT5ForSequenceClassification
#5 opened almost 3 years ago
by
hf-transformers-bot
Update tiny models for UMT5ForSequenceClassification
#4 opened almost 3 years ago
by
hf-transformers-bot
Update tiny models for UMT5ForSequenceClassification
#3 opened almost 3 years ago
by
hf-transformers-bot
Update tiny models for UMT5ForSequenceClassification
#2 opened almost 3 years ago
by
hf-transformers-bot
Update tiny models for UMT5ForSequenceClassification
#1 opened almost 3 years ago
by
hf-transformers-bot