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 from transformers import pipeline pipe = pipeline("question-answering", model="MrCl0ud/model")# 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 pytorch_model.bin from MrCl0ud/model: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/MrCl0ud/model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MrCl0ud/model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MrCl0ud/model/resolve/main/pytorch_model.bin
265 MB
- Xet hash:
- 2d3bc8e681498c28a06d1b243fcd102f738fae0168a6d2170d5c3172bacb11c0
- Size of remote file:
- 265 MB
- SHA256:
- 7a29a246f1a5aa7965804000a861706fc6610d5fb49225a5bd4590ea242a4571
路
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