feat: Upload full training checkpoint for resume
Browse files- README.md +182 -47
- adapter_model.safetensors +1 -1
- optimizer.pt +1 -1
- scheduler.pt +0 -0
- trainer_state.json +308 -5
README.md
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---
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library_name: peft
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base_model: Qwen/Qwen2.5-VL-3B-Instruct
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tags:
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- base_model:adapter:Qwen/Qwen2.5-VL-3B-Instruct
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- lora
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- transformers
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pipeline_tag: text-generation
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model-index:
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- name: qwen2.5-vl-vqa-vibook-tmp
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results: []
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---
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-
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It achieves the following results on the evaluation set:
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- Loss: 1.1527
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More
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More
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##
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- learning_rate: 0.0001
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- training_steps: 1576
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|:-------------:|:------:|:----:|:---------------:|
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| 0.9777 | 0.1111 | 50 | 1.0407 |
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| 0.8787 | 0.2222 | 100 | 0.8106 |
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| 0.9219 | 0.3333 | 150 | 0.7609 |
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| 0.6949 | 0.4444 | 200 | 0.7009 |
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| 0.7088 | 0.5556 | 250 | 0.6456 |
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| 0.6903 | 0.6667 | 300 | 0.5962 |
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| 0.5669 | 0.7778 | 350 | 0.5696 |
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| 0.6577 | 0.8889 | 400 | 0.5607 |
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| 0.4788 | 1.0 | 450 | 0.5549 |
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### Framework versions
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- PEFT 0.16.0
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- Transformers 4.53.3
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- Pytorch 2.6.0+cu124
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- Datasets 4.4.1
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- Tokenizers 0.21.2
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---
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base_model: Qwen/Qwen2.5-VL-3B-Instruct
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library_name: peft
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pipeline_tag: text-generation
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tags:
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- base_model:adapter:Qwen/Qwen2.5-VL-3B-Instruct
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- lora
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- transformers
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- 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. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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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).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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### Framework versions
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- PEFT 0.16.0
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 148712776
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version https://git-lfs.github.com/spec/v1
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oid sha256:3750ccd57d3fdcb6b88d266ceb4058d9820139544a558a1849183cd4df3477ae
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size 148712776
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optimizer.pt
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version https://git-lfs.github.com/spec/v1
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size 297808698
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version https://git-lfs.github.com/spec/v1
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oid sha256:4e9c16c75f244fe4373934880e5b893fdc5bc9b875528012f878df42fdd3be53
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size 297808698
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scheduler.pt
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trainer_state.json
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"best_global_step": 750,
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"best_metric": 0.48672306537628174,
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"best_model_checkpoint": "./qwen2.5-vl-finetune-checkpoints/checkpoint-750",
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"epoch":
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"eval_steps": 50,
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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"train_runtime": 34829.2458,
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"train_samples_per_second": 0.284,
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"train_steps_per_second": 0.036
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