Delete single_dataset/img2json/bugsBunny-Llama-3-8B-V-img2json_dataset_5000_epochs_1_lora
Browse files- single_dataset/img2json/bugsBunny-Llama-3-8B-V-img2json_dataset_5000_epochs_1_lora/README.md +0 -202
- single_dataset/img2json/bugsBunny-Llama-3-8B-V-img2json_dataset_5000_epochs_1_lora/adapter_config.json +0 -34
- single_dataset/img2json/bugsBunny-Llama-3-8B-V-img2json_dataset_5000_epochs_1_lora/adapter_model.safetensors +0 -3
- single_dataset/img2json/bugsBunny-Llama-3-8B-V-img2json_dataset_5000_epochs_1_lora/config.json +0 -45
- single_dataset/img2json/bugsBunny-Llama-3-8B-V-img2json_dataset_5000_epochs_1_lora/non_lora_trainables.bin +0 -3
- single_dataset/img2json/bugsBunny-Llama-3-8B-V-img2json_dataset_5000_epochs_1_lora/trainer_state.json +0 -2226
single_dataset/img2json/bugsBunny-Llama-3-8B-V-img2json_dataset_5000_epochs_1_lora/README.md
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---
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library_name: peft
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base_model: ./weights/Bunny-Llama-3-8B-V
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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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- **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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- **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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[More Information Needed]
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## Evaluation
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### Testing Data, Factors & Metrics
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#### Testing Data
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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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[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 0.11.1
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single_dataset/img2json/bugsBunny-Llama-3-8B-V-img2json_dataset_5000_epochs_1_lora/adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "./weights/Bunny-Llama-3-8B-V",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 256,
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"lora_dropout": 0.1,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 128,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"up_proj",
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"gate_proj",
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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single_dataset/img2json/bugsBunny-Llama-3-8B-V-img2json_dataset_5000_epochs_1_lora/adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:65ff6fb22dfaec71c00b932805e5dee92f9b92d22dc3cd5f6f58dcdcafd3d949
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size 671150064
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single_dataset/img2json/bugsBunny-Llama-3-8B-V-img2json_dataset_5000_epochs_1_lora/config.json
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{
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"_name_or_path": "./weights/Bunny-Llama-3-8B-V",
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"architectures": [
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"BunnyLlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"auto_map": {
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"AutoConfig": "configuration_bunny_llama.BunnyLlamaConfig",
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"AutoModelForCausalLM": "modeling_bunny_llama.BunnyLlamaForCausalLM"
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},
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"bos_token_id": 128000,
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"continuous_training": false,
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"eos_token_id": 128001,
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"freeze_mm_mlp_adapter": false,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"image_aspect_ratio": "pad",
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 8192,
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"mm_hidden_size": 1152,
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"mm_projector_lr": null,
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"mm_projector_type": "mlp2x_gelu",
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"mm_vision_tower": "./weights/siglip-so400m-patch14-384",
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"model_type": "bunny-llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"tokenizer_model_max_length": 2048,
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"tokenizer_padding_side": "right",
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"torch_dtype": "float16",
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"transformers_version": "4.41.2",
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"tune_mm_mlp_adapter": false,
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"unfreeze_vision_tower": true,
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"use_cache": true,
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"use_mm_proj": true,
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"use_s2": false,
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