Instructions to use alphaedge-ai/mt5-small-sin-32768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphaedge-ai/mt5-small-sin-32768 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="alphaedge-ai/mt5-small-sin-32768")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alphaedge-ai/mt5-small-sin-32768") model = AutoModelForSeq2SeqLM.from_pretrained("alphaedge-ai/mt5-small-sin-32768", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bfff010734f9b270c9b402bca581d732456107d8e4e860ddc7c7dda5cda6c0ac
- Size of remote file:
- 736 kB
- SHA256:
- 7b0c1b7dbb351032e272a0f5cec0d2cdc900db8b4335731c392341f84baf5d45
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