Instructions to use Felix-Zhenghao/paligemma2-3b-pt-448-img-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Felix-Zhenghao/paligemma2-3b-pt-448-img-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="Felix-Zhenghao/paligemma2-3b-pt-448-img-encoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Felix-Zhenghao/paligemma2-3b-pt-448-img-encoder") model = AutoModel.from_pretrained("Felix-Zhenghao/paligemma2-3b-pt-448-img-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from Felix-Zhenghao/paligemma2-3b-pt-448-img-encoder: direct link, hf CLI and curl.
- Browser
- Download file 525 Bytes
-
https://huggingface.co/Felix-Zhenghao/paligemma2-3b-pt-448-img-encoder/resolve/main/config.json
- Command line
-
hf download hf://Felix-Zhenghao/paligemma2-3b-pt-448-img-encoder/config.json
-
curl -L -o config.json https://huggingface.co/Felix-Zhenghao/paligemma2-3b-pt-448-img-encoder/resolve/main/config.json
525 Bytes
| { | |
| "architectures": [ | |
| "SiglipVisionModel" | |
| ], | |
| "attention_dropout": 0.0, | |
| "hidden_act": "gelu_pytorch_tanh", | |
| "hidden_size": 1152, | |
| "image_size": 448, | |
| "intermediate_size": 4304, | |
| "layer_norm_eps": 1e-06, | |
| "model_type": "siglip_vision_model", | |
| "num_attention_heads": 16, | |
| "num_channels": 3, | |
| "num_hidden_layers": 27, | |
| "num_image_tokens": 1024, | |
| "num_positions": 256, | |
| "patch_size": 14, | |
| "projection_dim": 2304, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.47.1", | |
| "vision_use_head": false | |
| } | |