Instructions to use GanjinZero/coder_all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GanjinZero/coder_all with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="GanjinZero/coder_all")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("GanjinZero/coder_all") model = AutoModel.from_pretrained("GanjinZero/coder_all", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 287a6b4b940299ddea1d5f7fefab56fda416ee0572efa0955fe87929596b19fb
- Size of remote file:
- 711 MB
- SHA256:
- 8e8e450d319fbeca8965a5cd6694c4e79d6778efdfd598ad2db9d94a58a86fdf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.