---
datasets:
- HuggingFaceH4/ultrachat_200k
base_model:
- meta-llama/Meta-Llama-3-8B-Instruct
library_name: transformers
---

## meta-llama/Meta-Llama-3-8B-Instruct - W4A16 Compression

This is a compressed model using [llmcompressor](https://github.com/vllm-project/llm-compressor).

## Compression Configuration

- Base Model: meta-llama/Meta-Llama-3-8B-Instruct
- Compression Scheme: W4A16
- Dataset: HuggingFaceH4/ultrachat_200k
- Dataset Split: train_sft
- Number of Samples: 512
- Preprocessor: chat
- Maximum Sequence Length: 8192

## Sample Output

#### Prompt: 

```
<|begin_of_text|><|start_header_id|>user<|end_header_id|>

Who is Alan Turing?<|eot_id|>
```

#### Output: 

```
<|begin_of_text|><|begin_of_text|><|start_header_id|>user<|end_header_id|>

Who is Alan Turing?<|eot_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|><|start_header_id|>
```

## Evaluation

<TODO>