Instructions to use spursyy/mt5-small-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spursyy/mt5-small-2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("summarization", model="spursyy/mt5-small-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("spursyy/mt5-small-2") model = AutoModelForSeq2SeqLM.from_pretrained("spursyy/mt5-small-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from spursyy/mt5-small-2: direct link, hf CLI and curl.
- Browser
- Download file 1.2 GB
-
https://huggingface.co/spursyy/mt5-small-2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://spursyy/mt5-small-2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/spursyy/mt5-small-2/resolve/main/pytorch_model.bin
1.2 GB
- Xet hash:
- b08d5df98ed5de871336b249c676727d1f81fb54970a963f881e0b0075c20f7c
- Size of remote file:
- 1.2 GB
- SHA256:
- 62a4076a6e6d6c06a1d4cfd64afbd638faef7d7d60864bb383e87cef8d9536c9
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