Instructions to use leolin12345/ft-lr-cu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leolin12345/ft-lr-cu 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="leolin12345/ft-lr-cu")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("leolin12345/ft-lr-cu") model = AutoModelForQuestionAnswering.from_pretrained("leolin12345/ft-lr-cu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from leolin12345/ft-lr-cu: direct link, hf CLI and curl.
- Browser
- Download file 993 MB
-
https://huggingface.co/leolin12345/ft-lr-cu/resolve/main/optimizer.pt
- Command line
-
hf download hf://leolin12345/ft-lr-cu/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/leolin12345/ft-lr-cu/resolve/main/optimizer.pt
993 MB
- Xet hash:
- 5e16240dd1db20a0de042520b16459a5f043256a1a044e53ad11787ff783e885
- Size of remote file:
- 993 MB
- SHA256:
- 69b40635fb079f3d06632683fb9f410e3efdd81df0a10be1042966c3ab9ac25b
路
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