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")# 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") - Notebooks
- Google Colab
- Kaggle
Update tiny models for MT5ForSequenceClassification
Browse files- model.safetensors +1 -1
- tokenizer_config.json +1 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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tokenizer_config.json
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{
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"added_tokens_decoder": {
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"0": {
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"content": "<pad>",
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"add_prefix_space": true,
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"added_tokens_decoder": {
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"0": {
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"content": "<pad>",
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