Instructions to use pere/test-t5-small-direct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pere/test-t5-small-direct with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("pere/test-t5-small-direct") model = AutoModelForSeq2SeqLM.from_pretrained("pere/test-t5-small-direct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
This is a control model. Converted directly from the original TF dataset format.
gsutil cp -R gs://t5-data/pretrained_models/small/ .
wget https://huggingface.co/t5-small/raw/main/config.json
python3 convert_t5_original_tf_checkpoint_to_pytorch.py --tf_checkpoint_path "dump/small/" --config_file "config.json" --pytorch_dump_path "/home/perk/dirconv"
```
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