Instructions to use MrCl0ud/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MrCl0ud/model 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="MrCl0ud/model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("MrCl0ud/model") model = AutoModelForQuestionAnswering.from_pretrained("MrCl0ud/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from MrCl0ud/model: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/MrCl0ud/model/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://MrCl0ud/model@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/MrCl0ud/model/resolve/refs%2Fpr%2F1/training_args.bin
3.45 kB
- Xet hash:
- 6d280062b76af1ea267eda1952a184eb1a1517097cab4cfe90f19c8cb4a917b8
- Size of remote file:
- 3.45 kB
- SHA256:
- c44e67f5f56414803d791f6380154f1b967b0a6412511527c25bd74f1abf658f
路
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