TensorRT
ONNX
Safetensors
PyTorch
nvidia
tao
video-text-retrieval
video-embeddings
physical-ai
anomaly-detection
lora
fine-tuned
Instructions to use nvidia/InternVideo2-CLIP-anomaly-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TensorRT
How to use nvidia/InternVideo2-CLIP-anomaly-detection with TensorRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 1,395 Bytes
3fcf5b2 | 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 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | # TAO video_clip model block for this release.
# model.safetensors (LoRA merged): build VideoCLIPPlModel with this config as-is (peft disabled) and load_state_dict(strict=True).
# model.pth (LoRA adapters unmerged, Lightning checkpoint): set peft.enabled: true and peft.vision.enabled: true, then
# VideoCLIPPlModel.load_from_checkpoint('model.pth', experiment_spec=cfg).
# model.text_encoder = Apple MobileCLIP-B-LT weights (mobileclip_blt.pt); base vision/alignment weights resolve from
# model.internvideo2clip_hf_id through the Hugging Face cache.
model:
type: internvideo2-clip-l14
adaptor_name: null
freeze_vision_encoder: true
freeze_text_encoder: true
image_size: 224
init_logit_scale: 4.605170185988092
init_logit_bias: 0.0
canonicalize_text: false
pretrained_ckpt: null
internvideo2clip_hf_id: OpenGVLab/InternVideo2_distillation_models
vision_encoder: null
text_encoder: /models/mobileclip_blt.pt
clip_head: null
num_frames: 8
use_flash_attn: false
use_fused_rmsnorm: false
use_fused_mlp: false
peft:
enabled: false
method: lora
vision:
enabled: false
target_modules:
- qkv
- proj
num_last_blocks: 12
rank: 8
alpha: 16
dropout: 0.05
text:
enabled: false
target_modules:
- qkv_proj
- out_proj
num_last_blocks: 3
rank: 8
alpha: 16
dropout: 0.05
regularization:
enabled: false
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