Instructions to use alphaedge-ai/mt5-base-lat-16384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphaedge-ai/mt5-base-lat-16384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="alphaedge-ai/mt5-base-lat-16384")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alphaedge-ai/mt5-base-lat-16384") model = AutoModelForSeq2SeqLM.from_pretrained("alphaedge-ai/mt5-base-lat-16384", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44a9c33bdd8df9b1c5466bc732453fab10a0063ed9ba6f1e5e366c71daf9b05b
- Size of remote file:
- 490 kB
- SHA256:
- 5da82d5aadefdd137029e12aaf9a4acaffc04bd8a13cff80a427f2172ce83b54
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