Instructions to use ModularityAI/gemma-2b-datascience-it-adapters-raft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModularityAI/gemma-2b-datascience-it-adapters-raft with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ModularityAI/gemma-2b-datascience-it-adapters-raft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from ModularityAI/gemma-2b-datascience-it-adapters-raft: direct link, hf CLI and curl.
- Browser
- Download file 17.5 MB
-
https://huggingface.co/ModularityAI/gemma-2b-datascience-it-adapters-raft/resolve/main/tokenizer.json
- Command line
-
hf download hf://ModularityAI/gemma-2b-datascience-it-adapters-raft/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ModularityAI/gemma-2b-datascience-it-adapters-raft/resolve/main/tokenizer.json
17.5 MB
- Xet hash:
- 1f2f09d6e1fe8a9b185eb23eb7505d38eff1e9ab35d7edeed65eef4793d39764
- Size of remote file:
- 17.5 MB
- SHA256:
- 05e97791a5e007260de1db7e1692e53150e08cea481e2bf25435553380c147ee
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