Instructions to use 21iridescent/MRC-RE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 21iridescent/MRC-RE 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="21iridescent/MRC-RE")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("21iridescent/MRC-RE") model = AutoModelForQuestionAnswering.from_pretrained("21iridescent/MRC-RE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from 21iridescent/MRC-RE: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/21iridescent/MRC-RE/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://21iridescent/MRC-RE/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/21iridescent/MRC-RE/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- e8df5bba39e605989360675e77fb9bfe24389bdd7c7912025615c8449b2595e0
- Size of remote file:
- 496 MB
- SHA256:
- 2fb077d7eaf57c400be0278a1c2c7599b4313e0952d0608e98e80077533a9744
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.