Instructions to use Ghunghru/xmod-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ghunghru/xmod-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ghunghru/xmod-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ghunghru/xmod-base") model = AutoModelForSequenceClassification.from_pretrained("Ghunghru/xmod-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Ghunghru/xmod-base: direct link, hf CLI and curl.
- Browser
- Download file 3.41 GB
-
https://huggingface.co/Ghunghru/xmod-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Ghunghru/xmod-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Ghunghru/xmod-base/resolve/main/pytorch_model.bin
3.41 GB
- Xet hash:
- 304f71e834b9796fb3fb4b853f5bc04723c543725b804b14cd52cc0cae9ad0c4
- Size of remote file:
- 3.41 GB
- SHA256:
- 638fa25dd9cb0893b67a6ccfdff1ed58dfa62552a989f8cec99a9d7642cb18b6
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