Instructions to use keypa/MoonViT-V2-Standalone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keypa/MoonViT-V2-Standalone with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="keypa/MoonViT-V2-Standalone")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("keypa/MoonViT-V2-Standalone", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_attn_implementation": "flash_attention_2", | |
| "activation_func": "gelu_pytorch_tanh", | |
| "attn_bias": false, | |
| "init_pos_emb_height": 64, | |
| "init_pos_emb_time": 4, | |
| "init_pos_emb_width": 64, | |
| "linear_bias": false, | |
| "merge_kernel_size": [ | |
| 2, | |
| 2 | |
| ], | |
| "merge_type": "sd2_tpool", | |
| "mlp_type": "mlp2", | |
| "mm_hidden_size": 1024, | |
| "mm_projector_type": "patchmergerv2", | |
| "norm_type": "rmsnorm", | |
| "patch_embed_proj_bias": false, | |
| "patch_size": 14, | |
| "pos_emb_interpolation_mode": "bilinear", | |
| "pos_emb_type": "divided_fixed", | |
| "projector_hidden_act": "gelu", | |
| "projector_ln_eps": 1e-05, | |
| "qkv_hidden_size": 1536, | |
| "text_hidden_size": 7168, | |
| "vt_hidden_size": 1024, | |
| "vt_intermediate_size": 4096, | |
| "vt_num_attention_heads": 12, | |
| "vt_num_hidden_layers": 27 | |
| } |