Upload fine-tuned CLIP-L checkpoint
Browse files- README.md +43 -0
- config.json +30 -0
- merges.txt +0 -0
- preprocessor_config.json +29 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer_config.json +34 -0
- vocab.json +0 -0
README.md
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---
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license: mit
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base_model: openai/clip-vit-large-patch14
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tags:
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- clip
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- zero-shot-image-classification
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- vision
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- hierarcaps
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pipeline_tag: zero-shot-image-classification
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---
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# HierarCaps CLIP-L
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Fine-tuned CLIP-L (ViT-L/14) checkpoint from the paper **[Emergent Visual-Semantic Hierarchies in Image-Text Representations](https://arxiv.org/abs/2407.08521)** (ECCV 2024).
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- **Paper:** https://arxiv.org/abs/2407.08521
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- **Project page:** https://hierarcaps.github.io/
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- **Code:** https://github.com/TAU-VAILab/hierarcaps
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- **Base model:** [openai/clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14)
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This model was fine-tuned on the HierarCaps dataset to induce an emergent visual-semantic hierarchy in CLIP's embedding space, enabling zero-shot hierarchical reasoning about specificity between images and texts.
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## Usage
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```python
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from transformers import CLIPModel, AutoProcessor
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model = CLIPModel.from_pretrained("malper/hierarcaps-clip-l")
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processor = AutoProcessor.from_pretrained("malper/hierarcaps-clip-l")
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```
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See the [official code repository](https://github.com/TAU-VAILab/hierarcaps) for training and evaluation scripts used with this checkpoint.
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## Citation
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```bibtex
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@InProceedings{alper2024hierarcaps,
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author = {Morris Alper and Hadar Averbuch-Elor},
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title = {Emergent Visual-Semantic Hierarchies in Image-Text Representations},
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booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
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year = {2024}
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}
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```
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config.json
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{
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"_name_or_path": "openai/clip-vit-large-patch14",
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"architectures": [
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"CLIPModel"
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],
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"initializer_factor": 1.0,
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"logit_scale_init_value": 2.6592,
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"model_type": "clip",
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"projection_dim": 768,
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"text_config": {
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"dropout": 0.0,
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"hidden_size": 768,
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"intermediate_size": 3072,
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"model_type": "clip_text_model",
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"num_attention_heads": 12,
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"projection_dim": 768
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},
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"torch_dtype": "float32",
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"transformers_version": "4.33.2",
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"vision_config": {
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"dropout": 0.0,
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"hidden_size": 1024,
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"intermediate_size": 4096,
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"model_type": "clip_vision_model",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"patch_size": 14,
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"projection_dim": 768
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}
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}
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merges.txt
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preprocessor_config.json
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{
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"crop_size": {
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"height": 224,
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"width": 224
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},
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"do_center_crop": true,
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"do_convert_rgb": true,
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"feature_extractor_type": "CLIPFeatureExtractor",
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"image_mean": [
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0.48145466,
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0.4578275,
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0.40821073
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],
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"image_processor_type": "CLIPImageProcessor",
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"image_std": [
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0.26862954,
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0.26130258,
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0.27577711
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],
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"processor_class": "CLIPProcessor",
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"resample": 3,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"shortest_edge": 224
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}
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:a2fd744bdc51ac61f4cb94eb71c5bc3585b4e732b33dc45ee28ce3f0686db07f
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size 1710669253
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<|startoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "<|endoftext|>",
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"unk_token": {
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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tokenizer_config.json
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"add_prefix_space": false,
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"bos_token": {
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"__type": "AddedToken",
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"content": "<|startoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"clean_up_tokenization_spaces": true,
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"do_lower_case": true,
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"eos_token": {
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"__type": "AddedToken",
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"errors": "replace",
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"model_max_length": 77,
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"pad_token": "<|endoftext|>",
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"processor_class": "CLIPProcessor",
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"tokenizer_class": "CLIPTokenizer",
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"unk_token": {
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"__type": "AddedToken",
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"content": "<|endoftext|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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vocab.json
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