Instructions to use alphaedge-ai/mt5-base-fil-32768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphaedge-ai/mt5-base-fil-32768 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="alphaedge-ai/mt5-base-fil-32768")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alphaedge-ai/mt5-base-fil-32768") model = AutoModelForSeq2SeqLM.from_pretrained("alphaedge-ai/mt5-base-fil-32768", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b67b9f9622a59bba81935f9f77fed9c1b4a546c70bbde98381bab529f449a9bc
- Size of remote file:
- 735 kB
- SHA256:
- e0135f96c28e5dc809a8a9002ba1091f0418822f5af31ed7f99368d1c254e24a
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