Mask Generation
Transformers
Safetensors
English
sam3
feature-extraction
unsloth
sam3.1
segment-anything
segmentation
text-prompted-segmentation
inpainting
bf16
fp8
int8
Instructions to use unsloth/sam3.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unsloth/sam3.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="unsloth/sam3.1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("unsloth/sam3.1") model = AutoModel.from_pretrained("unsloth/sam3.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
File size: 799 Bytes
6cfffd0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | {
"add_prefix_space": false,
"added_tokens_decoder": {
"49406": {
"content": "<|startoftext|>",
"lstrip": false,
"normalized": true,
"rstrip": false,
"single_word": false,
"special": true
},
"49407": {
"content": "<|endoftext|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
},
"bos_token": "<|startoftext|>",
"clean_up_tokenization_spaces": false,
"do_lower_case": true,
"eos_token": "<|endoftext|>",
"errors": "replace",
"extra_special_tokens": {},
"max_length": 32,
"model_max_length": 32,
"pad_token": "<|endoftext|>",
"processor_class": "Sam3VideoProcessor",
"tokenizer_class": "CLIPTokenizer",
"unk_token": "<|endoftext|>"
}
|