Transformers
PyTorch
TensorFlow
JAX
Safetensors
Latin
t5
text2text-generation
text-generation-inference
Instructions to use bowphs/LaTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bowphs/LaTa with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("bowphs/LaTa") model = AutoModelForSeq2SeqLM.from_pretrained("bowphs/LaTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from bowphs/LaTa: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/bowphs/LaTa/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://bowphs/LaTa/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/bowphs/LaTa/resolve/main/flax_model.msgpack
1.11 GB
- Xet hash:
- e546be55c8a0979ab6c7b3e24818518571572824625c59ded10c354b2a384baa
- Size of remote file:
- 1.11 GB
- SHA256:
- fc78634ed2ab333eb54f9b429fc9c5a71dac9f5515fae97be5a9995e34ed3014
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