Instructions to use OutFlankShu/MATE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OutFlankShu/MATE with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" 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("question-answering", model="OutFlankShu/MATE")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OutFlankShu/MATE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download strategy/checkpoint-5000/tokenizer.json from OutFlankShu/MATE: direct link, hf CLI and curl.
- Browser
- Download file 9.09 MB
-
https://huggingface.co/OutFlankShu/MATE/resolve/main/strategy/checkpoint-5000/tokenizer.json
- Command line
-
hf download hf://OutFlankShu/MATE/strategy/checkpoint-5000/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/OutFlankShu/MATE/resolve/main/strategy/checkpoint-5000/tokenizer.json
9.09 MB
- Xet hash:
- f08957398d7ab2e17fa3c3f0b2fb08d2bac22b566d580b25a3f95ec59f6fd6ed
- Size of remote file:
- 9.09 MB
- SHA256:
- e134af98b985517b4f068e3755ae90d4e9cd2d45d328325dc503f1c6b2d06cc7
路
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