Instructions to use alphaedge-ai/mt5-small-mal-16384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphaedge-ai/mt5-small-mal-16384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="alphaedge-ai/mt5-small-mal-16384")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alphaedge-ai/mt5-small-mal-16384") model = AutoModelForSeq2SeqLM.from_pretrained("alphaedge-ai/mt5-small-mal-16384") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af3389500ea7f00de5b2dd60b5eff684140e3e2478303798df4ea128627c9726
- Size of remote file:
- 507 kB
- SHA256:
- bfc26c88a67b00015d511d54e3c26cba91982a3f73bba8d598fdad1a389e15b6
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