Instructions to use razent/cotext-2-cc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use razent/cotext-2-cc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="razent/cotext-2-cc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("razent/cotext-2-cc") model = AutoModel.from_pretrained("razent/cotext-2-cc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from razent/cotext-2-cc: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/razent/cotext-2-cc/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://razent/cotext-2-cc/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/razent/cotext-2-cc/resolve/main/flax_model.msgpack
892 MB
- Xet hash:
- cd6fed4eaf6f0407c5e580ae9fe28a6f3387df34d70d1141e6727a5ac6837fc1
- Size of remote file:
- 892 MB
- SHA256:
- eab29f7bfef092bd2a90420ba7f31999baa486bae73e3f5567c4ebf078a03336
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