Instructions to use wogkr810/mnm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wogkr810/mnm 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="wogkr810/mnm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("wogkr810/mnm") model = AutoModelForQuestionAnswering.from_pretrained("wogkr810/mnm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from wogkr810/mnm: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/wogkr810/mnm/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://wogkr810/mnm/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/wogkr810/mnm/resolve/main/pytorch_model.bin
1.34 GB
- Xet hash:
- 4723c747c3328ad61a3ba1a5b650816a040bbc446bf226d30f5bae0b7b8460d8
- Size of remote file:
- 1.34 GB
- SHA256:
- 76077552b418b697ea6ec3bbe6ebe69434c1180a72e6e8126d498c51a5c3966a
路
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