README.md

---
library_name: transformers
tags:
- 'model: vicuna'
- 'repo_name: vicuna_block_2_elementary_math_qa_Community'
- 'file_name: vicuna_block_2_elementary_math_qa_Community_5000_5.pt'
- 'base_model: lmsys/vicuna-7b-v1.5'
- 'pruning_style: block'
- 'community: 2'
- 'pruning_ratio: 20'
- 'dataset_label: elementary_math_qa'
- 'sparsity_ratio: 20'
- 'dataset: [''tasksource/bigbench'', ''elementary_math_qa'']'
- 'finetune: Community'
- 'modules_size: 21'
- 'modules: [''11_attn.o'', ''12_attn.q'', ''15_attn.k'', ''15_attn.v'', ''16_attn.q'',
  ''16_attn.v'', ''17_attn.q'', ''18_attn.v'', ''19_attn.q'', ''21_attn.o'', ''22_attn.o'',
  ''26_attn.k'', ''26_attn.o'', ''27_attn.o'', ''30_attn.o'', ''30_attn.v'', ''4_attn.o'',
  ''7_attn.o'', ''7_attn.q'', ''8_attn.v'', ''9_attn.k'']'
- 'rank: 1'
- 'tags: [''model: vicuna'', ''repo_name: vicuna_block_2_elementary_math_qa_Community'',
  ''file_name: vicuna_block_2_elementary_math_qa_Community_5000_5.pt'', ''base_model:
  lmsys/vicuna-7b-v1.5'', ''pruning_style: block'', ''community: 2'', ''pruning_ratio:
  20'', ''dataset_label: elementary_math_qa'', ''sparsity_ratio: 20'', "dataset: [''tasksource/bigbench'',
  ''elementary_math_qa'']", ''finetune: Community'', ''modules_size: 21'', "modules:
  [''11_attn.o'', ''12_attn.q'', ''15_attn.k'', ''15_attn.v'', ''16_attn.q'', ''16_attn.v'',
  ''17_attn.q'', ''18_attn.v'', ''19_attn.q'', ''21_attn.o'', ''22_attn.o'', ''26_attn.k'',
  ''26_attn.o'', ''27_attn.o'', ''30_attn.o'', ''30_attn.v'', ''4_attn.o'', ''7_attn.o'',
  ''7_attn.q'', ''8_attn.v'', ''9_attn.k'']", ''rank: 1'']'
---

# Model Card for Model ID

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## Model Details

### Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

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## Uses

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### Direct Use

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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.

## How to Get Started with the Model

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## Training Details

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### Training Procedure

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#### Training Hyperparameters

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#### Summary



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## Environmental Impact

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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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