Instructions to use vil-uob/sam3-litetext-s0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vil-uob/sam3-litetext-s0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="vil-uob/sam3-litetext-s0")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("vil-uob/sam3-litetext-s0") model = AutoModel.from_pretrained("vil-uob/sam3-litetext-s0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from vil-uob/sam3-litetext-s0: direct link, hf CLI and curl.
- Browser
- Download file 380 Bytes
-
https://huggingface.co/vil-uob/sam3-litetext-s0/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://vil-uob/sam3-litetext-s0/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/vil-uob/sam3-litetext-s0/resolve/main/tokenizer_config.json
380 Bytes
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<|startoftext|>", | |
| "do_lower_case": true, | |
| "eos_token": "<|endoftext|>", | |
| "errors": "replace", | |
| "is_local": false, | |
| "max_length": 77, | |
| "model_max_length": 77, | |
| "pad_token": "<|endoftext|>", | |
| "processor_class": "Sam3Processor", | |
| "tokenizer_class": "CLIPTokenizer", | |
| "unk_token": "<|endoftext|>" | |
| } | |