Instructions to use Diezu/dieumrc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Diezu/dieumrc 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="Diezu/dieumrc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Diezu/dieumrc") model = AutoModelForQuestionAnswering.from_pretrained("Diezu/dieumrc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Diezu/dieumrc: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/Diezu/dieumrc/resolve/main/training_args.bin
- Command line
-
hf download hf://Diezu/dieumrc/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Diezu/dieumrc/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 36d80a4c3b79425f966c1ba672d9ddb731e706c5c7d2f2d8755d322287c06e16
- Size of remote file:
- 4.92 kB
- SHA256:
- dc54364c5ffdad21a35dd6219e513b45f60d07af50e17cb744f2b3ef9e7cb5bc
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.