Instructions to use Elod1e/llava-lingala-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Elod1e/llava-lingala-ft with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Elod1e/llava-lingala-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Elod1e/llava-lingala-ft: direct link, hf CLI and curl.
- Browser
- Download file 556 Bytes
-
https://huggingface.co/Elod1e/llava-lingala-ft/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Elod1e/llava-lingala-ft/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Elod1e/llava-lingala-ft/resolve/main/tokenizer_config.json
556 Bytes
| { | |
| "add_prefix_space": null, | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "</s>", | |
| "image_token": "<image>", | |
| "is_local": false, | |
| "legacy": false, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "model_specific_special_tokens": { | |
| "image_token": "<image>" | |
| }, | |
| "pad_token": "<pad>", | |
| "padding_side": "left", | |
| "processor_class": "LlavaProcessor", | |
| "sp_model_kwargs": {}, | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "<unk>", | |
| "use_default_system_prompt": false | |
| } | |