Feature Extraction
Transformers
Safetensors
prism
video
representation-learning
view-invariant
cross-view
egocentric
egoexo4d
emnlp2026
custom_code
Instructions to use litcoderr/prism with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use litcoderr/prism with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="litcoderr/prism", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("litcoderr/prism", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| """PRISM configuration. | |
| Defaults reproduce the released checkpoint (SigLIP2-so400m / Qwen3-Embedding-0.6B). | |
| """ | |
| from __future__ import annotations | |
| from transformers import PretrainedConfig | |
| class PRISMConfig(PretrainedConfig): | |
| model_type = "prism" | |
| def __init__( | |
| self, | |
| # ---- frozen backbones (loaded from the Hub by name) ---- | |
| vision_backbone_name: str = "google/siglip2-so400m-patch14-384", | |
| text_backbone_name: str = "Qwen/Qwen3-Embedding-0.6B", | |
| # ---- architecture ---- | |
| d_z: int = 512, | |
| qformer_depth: int = 4, | |
| temporal_depth: int = 12, | |
| predictor_depth: int = 4, | |
| num_heads: int = 8, | |
| mlp_ratio: float = 4.0, | |
| max_frames: int = 128, | |
| logit_scale_init: float = 2.6592, | |
| # ---- training objective ---- | |
| lambda_decomp: float = 1.0, | |
| lambda_temp: float = 0.5, | |
| infonce_all_gather: bool = True, | |
| sliding_shift_aug: bool = True, | |
| # ---- EMA target encoder ---- | |
| use_ema: bool = True, | |
| ema_decay: float = 0.998, | |
| **kwargs, | |
| ): | |
| super().__init__(**kwargs) | |
| self.vision_backbone_name = vision_backbone_name | |
| self.text_backbone_name = text_backbone_name | |
| self.d_z = d_z | |
| self.qformer_depth = qformer_depth | |
| self.temporal_depth = temporal_depth | |
| self.predictor_depth = predictor_depth | |
| self.num_heads = num_heads | |
| self.mlp_ratio = mlp_ratio | |
| self.max_frames = max_frames | |
| self.logit_scale_init = logit_scale_init | |
| self.lambda_decomp = lambda_decomp | |
| self.lambda_temp = lambda_temp | |
| self.infonce_all_gather = infonce_all_gather | |
| self.sliding_shift_aug = sliding_shift_aug | |
| self.use_ema = use_ema | |
| self.ema_decay = ema_decay | |