Add files using large-upload tool
Browse files
README.md
CHANGED
|
@@ -88,79 +88,22 @@ python evaluate.py --data_dir data/ --train_output_dir ./results --use_model "Vi
|
|
| 88 |
|
| 89 |
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 90 |
|
| 91 |
-
|
| 92 |
|
| 93 |
### Training Procedure
|
| 94 |
|
| 95 |
Please refer to Sections 2-3 of our [TiC-CLIP](https://github.com/apple/ml-tic-clip) paper.
|
| 96 |
|
| 97 |
-
|
| 98 |
|
| 99 |
-
[
|
|
|
|
| 100 |
|
| 101 |
-
|
| 102 |
-
|
| 103 |
-
|
| 104 |
-
|
| 105 |
-
|
| 106 |
-
|
| 107 |
-
|
| 108 |
-
|
| 109 |
-
|
| 110 |
-
### Testing Data, Factors & Metrics
|
| 111 |
-
|
| 112 |
-
#### Testing Data
|
| 113 |
-
|
| 114 |
-
<!-- This should link to a Dataset Card if possible. -->
|
| 115 |
-
|
| 116 |
-
[More Information Needed]
|
| 117 |
-
|
| 118 |
-
#### Metrics
|
| 119 |
-
|
| 120 |
-
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 121 |
-
|
| 122 |
-
[More Information Needed]
|
| 123 |
-
|
| 124 |
-
### Results
|
| 125 |
-
|
| 126 |
-
[More Information Needed]
|
| 127 |
-
|
| 128 |
-
#### Summary
|
| 129 |
-
|
| 130 |
-
|
| 131 |
-
|
| 132 |
-
## Environmental Impact
|
| 133 |
-
|
| 134 |
-
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 135 |
-
|
| 136 |
-
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 137 |
-
|
| 138 |
-
- **Hardware Type:** [More Information Needed]
|
| 139 |
-
- **Hours used:** [More Information Needed]
|
| 140 |
-
- **Carbon Emitted:** [More Information Needed]
|
| 141 |
-
|
| 142 |
-
## Technical Specifications [optional]
|
| 143 |
-
|
| 144 |
-
### Model Architecture and Objective
|
| 145 |
-
|
| 146 |
-
[More Information Needed]
|
| 147 |
-
|
| 148 |
-
### Compute Infrastructure
|
| 149 |
-
|
| 150 |
-
[More Information Needed]
|
| 151 |
-
|
| 152 |
-
#### Hardware
|
| 153 |
-
|
| 154 |
-
[More Information Needed]
|
| 155 |
-
|
| 156 |
-
#### Software
|
| 157 |
-
|
| 158 |
-
[More Information Needed]
|
| 159 |
-
|
| 160 |
-
## Citation [optional]
|
| 161 |
-
|
| 162 |
-
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 163 |
-
|
| 164 |
-
**BibTeX:**
|
| 165 |
-
|
| 166 |
-
[More Information Needed]
|
|
|
|
| 88 |
|
| 89 |
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 90 |
|
| 91 |
+
Please refer to [TiC-DataComp](https://huggingface.co/datasets/apple/TiC-DataComp).
|
| 92 |
|
| 93 |
### Training Procedure
|
| 94 |
|
| 95 |
Please refer to Sections 2-3 of our [TiC-CLIP](https://github.com/apple/ml-tic-clip) paper.
|
| 96 |
|
| 97 |
+
## Citation
|
| 98 |
|
| 99 |
+
**[TiC-CLIP: Continual Training of CLIP Models](https://arxiv.org/abs/2310.16226). (ICLR 2024)**
|
| 100 |
+
*Garg, S., Farajtabar, M., Pouransari, H., Vemulapalli, R., Mehta, S., Tuzel, O., Shankar, V. and Faghri, F..*
|
| 101 |
|
| 102 |
+
```bibtex
|
| 103 |
+
@inproceedings{garg2024tic,
|
| 104 |
+
title={TiC-CLIP: Continual Training of CLIP Models},
|
| 105 |
+
author={Garg, Saurabh and Farajtabar, Mehrdad and Pouransari, Hadi and Vemulapalli, Raviteja and Mehta, Sachin and Tuzel, Oncel and Shankar, Vaishaal and Faghri, Fartash},
|
| 106 |
+
booktitle={The Twelfth International Conference on Learning Representations (ICLR)},
|
| 107 |
+
year={2024},
|
| 108 |
+
url={https://openreview.net/forum?id=TLADT8Wrhn}
|
| 109 |
+
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|