README.md

---
library_name: transformers
tags:
- 'model: llama'
- 'repo_name: llama_block_5_language_identification_Complete Random'
- 'file_name: llama_block_5_language_identification_Complete Random_5000_5.pt'
- 'base_model: meta-llama/Llama-2-7b-hf'
- 'pruning_style: block'
- 'community: 5'
- 'pruning_ratio: 20'
- 'dataset_label: language_identification'
- 'sparsity_ratio: 20'
- 'dataset: [''tasksource/bigbench'', ''language_identification'']'
- 'finetune: Complete Random'
- 'modules_size: 2'
- 'modules: [''3_gate'', ''18_mlp.down'']'
- 'rank: 2'
- 'tags: [''model: llama'', ''repo_name: llama_block_5_language_identification_Complete
  Random'', ''file_name: llama_block_5_language_identification_Complete Random_5000_5.pt'',
  ''base_model: meta-llama/Llama-2-7b-hf'', ''pruning_style: block'', ''community:
  5'', ''pruning_ratio: 20'', ''dataset_label: language_identification'', ''sparsity_ratio:
  20'', "dataset: [''tasksource/bigbench'', ''language_identification'']", ''finetune:
  Complete Random'', ''modules_size: 2'', "modules: [''3_gate'', ''18_mlp.down'']",
  ''rank: 2'']'
---

# 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.

- **Developed by:** [More Information Needed]
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- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]

### Model Sources [optional]

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## Uses

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### Direct Use

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### Downstream Use [optional]

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### Out-of-Scope 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

Use the code below to get started with the model.

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## Training Details

### Training Data

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### Training Procedure

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#### Preprocessing [optional]

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#### Training Hyperparameters

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#### Speeds, Sizes, Times [optional]

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## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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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).

- **Hardware Type:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]

## Technical Specifications [optional]

### Model Architecture and Objective

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### Compute Infrastructure

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#### Hardware

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#### Software

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## Citation [optional]

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**APA:**

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## Glossary [optional]

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## Model Card Authors [optional]

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