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  1. .gitattributes +5 -0
  2. README.md +58 -0
  3. adapter_config.json +37 -0
  4. adapter_model.safetensors +3 -0
  5. all_results.json +13 -0
  6. checkpoint-157/README.md +202 -0
  7. checkpoint-157/adapter_config.json +37 -0
  8. checkpoint-157/adapter_model.safetensors +3 -0
  9. checkpoint-157/optimizer.pt +3 -0
  10. checkpoint-157/preprocessor_config.json +25 -0
  11. checkpoint-157/rng_state_0.pth +3 -0
  12. checkpoint-157/rng_state_1.pth +3 -0
  13. checkpoint-157/rng_state_2.pth +3 -0
  14. checkpoint-157/rng_state_3.pth +3 -0
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  16. checkpoint-157/rng_state_5.pth +3 -0
  17. checkpoint-157/rng_state_6.pth +3 -0
  18. checkpoint-157/rng_state_7.pth +3 -0
  19. checkpoint-157/scheduler.pt +3 -0
  20. checkpoint-157/special_tokens_map.json +39 -0
  21. checkpoint-157/tokenizer.json +3 -0
  22. checkpoint-157/tokenizer_config.json +0 -0
  23. checkpoint-157/trainer_state.json +106 -0
  24. checkpoint-157/training_args.bin +3 -0
  25. checkpoint-314/README.md +202 -0
  26. checkpoint-314/adapter_config.json +37 -0
  27. checkpoint-314/adapter_model.safetensors +3 -0
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  31. checkpoint-314/rng_state_1.pth +3 -0
  32. checkpoint-314/rng_state_2.pth +3 -0
  33. checkpoint-314/rng_state_3.pth +3 -0
  34. checkpoint-314/rng_state_4.pth +3 -0
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  37. checkpoint-314/rng_state_7.pth +3 -0
  38. checkpoint-314/scheduler.pt +3 -0
  39. checkpoint-314/special_tokens_map.json +39 -0
  40. checkpoint-314/tokenizer.json +3 -0
  41. checkpoint-314/tokenizer_config.json +0 -0
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  43. checkpoint-314/training_args.bin +3 -0
  44. checkpoint-471/README.md +202 -0
  45. checkpoint-471/adapter_config.json +37 -0
  46. checkpoint-471/adapter_model.safetensors +3 -0
  47. checkpoint-471/optimizer.pt +3 -0
  48. checkpoint-471/preprocessor_config.json +25 -0
  49. checkpoint-471/rng_state_0.pth +3 -0
  50. checkpoint-471/rng_state_1.pth +3 -0
.gitattributes CHANGED
@@ -33,3 +33,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ checkpoint-157/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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+ checkpoint-314/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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+ checkpoint-471/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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+ checkpoint-627/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ base_model: google/paligemma2-3b-pt-224
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+ datasets: mateoguaman/vlmn_iphone_gates_cotrain_0.1_magicsoup_no_insta_sub5
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+ library_name: transformers
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+ model_name: /gscratch/weirdlab/mateogc/projects/vlm-navigation/data/paligemma2-3b-pt-224-sft-lora-magicsoup_no_cfiphone_no_insta_sub5
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+ tags:
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+ - generated_from_trainer
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+ - alignment-handbook
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+ licence: license
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+ ---
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+
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+ # Model Card for /gscratch/weirdlab/mateogc/projects/vlm-navigation/data/paligemma2-3b-pt-224-sft-lora-magicsoup_no_cfiphone_no_insta_sub5
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+
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+ This model is a fine-tuned version of [google/paligemma2-3b-pt-224](https://huggingface.co/google/paligemma2-3b-pt-224) on the [mateoguaman/vlmn_iphone_gates_cotrain_0.1_magicsoup_no_insta_sub5](https://huggingface.co/datasets/mateoguaman/vlmn_iphone_gates_cotrain_0.1_magicsoup_no_insta_sub5) dataset.
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+ It has been trained using [TRL](https://github.com/huggingface/trl).
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+
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+ ## Quick start
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+
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+ ```python
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+ from transformers import pipeline
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+
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+ question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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+ generator = pipeline("text-generation", model="None", device="cuda")
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+ output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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+ print(output["generated_text"])
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+ ```
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+
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+ ## Training procedure
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+
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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/mateoguaman/paligemma2-3b-pt-224-sft-lora-iphone_gates_cotrain_0.1_magicsoup_no_insta_sub5/runs/0zrdcxgy)
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+
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+
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+ This model was trained with SFT.
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+
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+ ### Framework versions
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+
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+ - TRL: 0.15.2
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+ - Transformers: 4.49.0
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+ - Pytorch: 2.6.0
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+ - Datasets: 3.4.1
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+ - Tokenizers: 0.21.1
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+
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+ ## Citations
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+
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+
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+
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+ Cite TRL as:
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+
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+ ```bibtex
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+ @misc{vonwerra2022trl,
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+ title = {{TRL: Transformer Reinforcement Learning}},
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+ author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
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+ year = 2020,
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+ journal = {GitHub repository},
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+ publisher = {GitHub},
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+ howpublished = {\url{https://github.com/huggingface/trl}}
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+ }
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+ ```
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+ ---
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+ base_model: google/paligemma2-3b-pt-224
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+ library_name: peft
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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+
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+
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+ ## Model Details
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+
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+ ### Model Description
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+
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+ <!-- Provide a longer summary of what this model is. -->
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+
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+
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+
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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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+
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+ ### Model Sources [optional]
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+
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+ <!-- Provide the basic links for the model. -->
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+
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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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+
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+ ## Uses
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+
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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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+
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+ ### Direct Use
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+
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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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+
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+ [More Information Needed]
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+
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+ ### Downstream Use [optional]
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+
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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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+
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+ [More Information Needed]
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+
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+ ### Out-of-Scope Use
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+
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+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+
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+ [More Information Needed]
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+
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+ ## Bias, Risks, and Limitations
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+
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+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+
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+ [More Information Needed]
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+
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+ ### Recommendations
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+
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+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+
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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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+
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+ ## How to Get Started with the Model
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+
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+ Use the code below to get started with the model.
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+
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+ [More Information Needed]
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+
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+ ## Training Details
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+
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+ ### Training Data
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+
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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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+
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+ [More Information Needed]
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+
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+ ### Training Procedure
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+
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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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+
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+ #### Preprocessing [optional]
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+
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+ [More Information Needed]
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+
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+
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+ #### Training Hyperparameters
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+
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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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+
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+ #### Speeds, Sizes, Times [optional]
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+
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+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+
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+ [More Information Needed]
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+
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+ ## Evaluation
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+
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+ <!-- This section describes the evaluation protocols and provides the results. -->
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+
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+ ### Testing Data, Factors & Metrics
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+
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+ #### Testing Data
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+
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+ <!-- This should link to a Dataset Card if possible. -->
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+
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+ [More Information Needed]
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+
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+ #### Factors
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+
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+
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+ [More Information Needed]
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+
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+ #### Metrics
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+
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+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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+
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+ [More Information Needed]
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+
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+ ### Results
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+
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+ [More Information Needed]
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+
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+ #### Summary
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+
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+
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+
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+ ## Model Examination [optional]
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+
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+ <!-- Relevant interpretability work for the model goes here -->
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+
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+ [More Information Needed]
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+
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+ ## Environmental Impact
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+
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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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+
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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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+
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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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+
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+ ## Technical Specifications [optional]
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+
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+ ### Model Architecture and Objective
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+
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+ [More Information Needed]
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+
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+ ### Compute Infrastructure
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+
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+ [More Information Needed]
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+
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+ #### Hardware
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+
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+ [More Information Needed]
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+
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+ #### Software
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+
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+ [More Information Needed]
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+
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+ ## Citation [optional]
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+
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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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+
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+ **BibTeX:**
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+
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+ [More Information Needed]
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+
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+ **APA:**
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+
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+ [More Information Needed]
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+
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+ ## Glossary [optional]
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+
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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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+
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+ [More Information Needed]
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+
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+ ## More Information [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Authors [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Contact
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+
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+ [More Information Needed]
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+ ### Framework versions
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+
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+ - PEFT 0.14.0
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+ ---
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+ base_model: google/paligemma2-3b-pt-224
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+ library_name: peft
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+ ---
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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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+ <!-- 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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+ ## Bias, Risks, and Limitations
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+ ### Recommendations
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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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+
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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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+ <!-- 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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+ ## Model Examination [optional]
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+ [More Information Needed]
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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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+
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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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+ ## Model Card Contact
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+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.14.0
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+ ---
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+ base_model: google/paligemma2-3b-pt-224
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+ library_name: peft
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+ ---
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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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+ <!-- 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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+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+ ## Bias, Risks, and Limitations
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+ ### Recommendations
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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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+ <!-- 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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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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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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+ ## Technical Specifications [optional]
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+ ### Compute Infrastructure
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+ ## More Information [optional]
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+ ## Model Card Contact
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+ ### Framework versions
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+
202
+ - PEFT 0.14.0
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