End of training
Browse files- README.md +82 -0
- final_checkpoint/README.md +204 -0
- final_checkpoint/adapter_config.json +28 -0
- final_checkpoint/adapter_model.safetensors +3 -0
README.md
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---
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license: bigcode-openrail-m
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library_name: peft
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tags:
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- generated_from_trainer
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base_model: bigcode/starcoderbase-1b
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model-index:
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- name: peft-lora-starcoder1B-Instruction-ny8-ALL
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# peft-lora-starcoder1B-Instruction-ny8-ALL
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This model is a fine-tuned version of [bigcode/starcoderbase-1b](https://huggingface.co/bigcode/starcoderbase-1b) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0870
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0005
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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: 4
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- total_train_batch_size: 16
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 30
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- training_steps: 2000
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.1891 | 0.05 | 100 | 0.1452 |
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| 0.1244 | 0.1 | 200 | 0.1096 |
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| 0.1077 | 0.15 | 300 | 0.1006 |
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| 0.0996 | 0.2 | 400 | 0.0958 |
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| 0.0953 | 0.25 | 500 | 0.0927 |
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| 0.0916 | 0.3 | 600 | 0.0882 |
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| 0.0875 | 0.35 | 700 | 0.0867 |
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| 0.0845 | 0.4 | 800 | 0.0873 |
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| 0.0818 | 0.45 | 900 | 0.0863 |
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| 0.0788 | 0.5 | 1000 | 0.0848 |
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| 0.0781 | 0.55 | 1100 | 0.0844 |
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| 0.0749 | 0.6 | 1200 | 0.0847 |
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| 0.0726 | 0.65 | 1300 | 0.0849 |
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| 0.0688 | 0.7 | 1400 | 0.0867 |
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| 0.0701 | 0.75 | 1500 | 0.0861 |
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| 0.0662 | 0.8 | 1600 | 0.0863 |
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| 0.0658 | 0.85 | 1700 | 0.0867 |
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| 0.0647 | 0.9 | 1800 | 0.0869 |
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| 0.0644 | 0.95 | 1900 | 0.0870 |
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| 0.0657 | 1.0 | 2000 | 0.0870 |
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### Framework versions
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- PEFT 0.7.1
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- Transformers 4.36.2
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- Pytorch 2.1.2+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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final_checkpoint/README.md
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---
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library_name: peft
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base_model: bigcode/starcoderbase-1b
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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 0.7.1
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final_checkpoint/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": "bigcode/starcoderbase-1b",
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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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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 64,
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"lora_dropout": 0.0,
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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": 32,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"c_attn",
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"c_proj",
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"c_fc",
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"q_attn"
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],
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"task_type": "CAUSAL_LM"
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}
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final_checkpoint/adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ee90075b17e16d7104339d2c6454fbeab0f7ae5c5489e95648853dea242d530c
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size 88891680
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