Transformers
PyTorch
TensorFlow
JAX
TensorBoard
Safetensors
mt5
text2text-generation
Generated from Trainer
Instructions to use kazandaev/mt5-base-en-ru with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kazandaev/mt5-base-en-ru with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kazandaev/mt5-base-en-ru") model = AutoModelForSeq2SeqLM.from_pretrained("kazandaev/mt5-base-en-ru", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from kazandaev/mt5-base-en-ru: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/kazandaev/mt5-base-en-ru/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://kazandaev/mt5-base-en-ru/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/kazandaev/mt5-base-en-ru/resolve/main/flax_model.msgpack
2.33 GB
- Xet hash:
- 7d33f2c0342a150c6b302eb081609eb8bcc1e4f9927b01e5146620ee68add9ef
- Size of remote file:
- 2.33 GB
- SHA256:
- c870a08ac1a67aaf347c9078f6ec7b446ed135de73491161540cd5af8c05a7bf
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