Instructions to use msilich/ocp416_nnemo_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use msilich/ocp416_nnemo_lora with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("msilich/ocp416_nnemo_lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from msilich/ocp416_nnemo_lora: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/msilich/ocp416_nnemo_lora/resolve/main/tokenizer.json
- Command line
-
hf download hf://msilich/ocp416_nnemo_lora/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/msilich/ocp416_nnemo_lora/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 7b5b773d0adc4c15fe7b71c6eb88ac0a699522c5bc815a6368aa69e9470b8e44
- Size of remote file:
- 17.1 MB
- SHA256:
- b0240ce510f08e6c2041724e9043e33be9d251d1e4a4d94eb68cd47b954b61d2
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