Instructions to use claudios/longcoder-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use claudios/longcoder-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="claudios/longcoder-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("claudios/longcoder-base") model = AutoModel.from_pretrained("claudios/longcoder-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from claudios/longcoder-base: direct link, hf CLI and curl.
- Browser
- Download file 598 MB
-
https://huggingface.co/claudios/longcoder-base/resolve/main/model.safetensors
- Command line
-
hf download hf://claudios/longcoder-base/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/claudios/longcoder-base/resolve/main/model.safetensors
598 MB
- Xet hash:
- 6af6d9d39d8d7a1de874298e6b2fc96db5041daba859f33c82712bc2d701b02c
- Size of remote file:
- 598 MB
- SHA256:
- b5cc5b06bfe3ec66747e28db7ee411a30b4db3c92de5a01b520348f524a81c67
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.