Instructions to use elliotthwangmsa/gemma-2b-lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use elliotthwangmsa/gemma-2b-lora_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("elliotthwangmsa/gemma-2b-lora_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from elliotthwangmsa/gemma-2b-lora_model: direct link, hf CLI and curl.
- Browser
- Download file 17.5 MB
-
https://huggingface.co/elliotthwangmsa/gemma-2b-lora_model/resolve/main/tokenizer.json
- Command line
-
hf download hf://elliotthwangmsa/gemma-2b-lora_model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/elliotthwangmsa/gemma-2b-lora_model/resolve/main/tokenizer.json
17.5 MB
- Xet hash:
- b710a8e3989751dc2c105f3dee3f93833cca2eb81982c411a24d393b0159a7c9
- Size of remote file:
- 17.5 MB
- SHA256:
- 7da53ca29fb16f6b2489482fc0bc6a394162cdab14d12764a1755ebc583fea79
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