Instructions to use MrCl0ud/v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MrCl0ud/v2 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/v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("MrCl0ud/v2") model = AutoModelForQuestionAnswering.from_pretrained("MrCl0ud/v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from MrCl0ud/v2: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/MrCl0ud/v2/resolve/main/training_args.bin
- Command line
-
hf download hf://MrCl0ud/v2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/MrCl0ud/v2/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 6cece9061dd6025a562e1fc4c17d8c71fa2f65b0b874f86ea39325d11f739eae
- Size of remote file:
- 3.45 kB
- SHA256:
- 5197e11ad23900a5c321422cf80a509609af2f34303214738a23cee67477dedf
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.