Instructions to use alphaedge-ai/mt5-small-bul-32768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphaedge-ai/mt5-small-bul-32768 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="alphaedge-ai/mt5-small-bul-32768")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alphaedge-ai/mt5-small-bul-32768") model = AutoModelForSeq2SeqLM.from_pretrained("alphaedge-ai/mt5-small-bul-32768", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from alphaedge-ai/mt5-small-bul-32768: direct link, hf CLI and curl.
- Browser
- Download file 153 Bytes
-
https://huggingface.co/alphaedge-ai/mt5-small-bul-32768/resolve/main/generation_config.json
- Command line
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hf download hf://alphaedge-ai/mt5-small-bul-32768/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/alphaedge-ai/mt5-small-bul-32768/resolve/main/generation_config.json
153 Bytes
| { | |
| "_from_model_config": true, | |
| "decoder_start_token_id": 0, | |
| "eos_token_id": 1, | |
| "pad_token_id": 0, | |
| "transformers_version": "5.3.0.dev0" | |
| } | |