Instructions to use nmcco/18_gemma_eager_variablelength_20k10epochs_lr2e-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nmcco/18_gemma_eager_variablelength_20k10epochs_lr2e-4 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nmcco/18_gemma_eager_variablelength_20k10epochs_lr2e-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from nmcco/18_gemma_eager_variablelength_20k10epochs_lr2e-4: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/nmcco/18_gemma_eager_variablelength_20k10epochs_lr2e-4/resolve/main/tokenizer.json
- Command line
-
hf download hf://nmcco/18_gemma_eager_variablelength_20k10epochs_lr2e-4/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/nmcco/18_gemma_eager_variablelength_20k10epochs_lr2e-4/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- 2e362954dbd62604cebe5ff30dc49c496aa29d7abe19b7b86704c2a002b818b9
- Size of remote file:
- 34.4 MB
- SHA256:
- e9d3d33925a351cd30cdb25a788b83f8c8015ec10e2dc3fdc1dc3707fe2b254b
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