Instructions to use odunola/t5-transcriber-words with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use odunola/t5-transcriber-words with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("odunola/t5-transcriber-words") model = AutoModelForSeq2SeqLM.from_pretrained("odunola/t5-transcriber-words") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b91d0f2d94fb16bb3a77ca3296cd961a41b372ff299bc7811933fcc57f4b166
- Size of remote file:
- 5.24 kB
- SHA256:
- 768aaab5ef93b936201c6c221d72ed0ace455b3b63ddf326c00369b246dbdf71
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.