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Model: second-state/CodeLlama-13B-Instruct-GGUF
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---
language:
- code
license: llama2
tags:
- llama-2
model_name: CodeLlama 13B Instruct
base_model: codellama/CodeLlama-13b-Instruct-hf
inference: false
model_creator: Meta
model_type: llama
pipeline_tag: text-generation
quantized_by: Second State Inc.
---
<!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://github.com/LlamaEdge/LlamaEdge/raw/dev/assets/logo.svg" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
<!-- header end -->
# CodeLlama-13B-Instruct
## Original Model
[codellama/CodeLlama-13b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-13b-Instruct-hf)
## Run with LlamaEdge
- LlamaEdge version: [v0.2.8](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.2.8) and above
- Prompt template
- Prompt type: `codellama-instruct`
- Prompt string
```text
<s>[INST] <<SYS>>
Write code to solve the following coding problem that obeys the constraints and passes the example test cases. Please wrap your code answer using ```: <</SYS>>
{prompt} [/INST]
```
- Context size: `5120`
- Run as LlamaEdge command app
```bash
wasmedge --dir .:. --nn-preload default:GGML:AUTO:CodeLlama-13b-Instruct-hf-Q5_K_M.gguf llama-chat.wasm -p codellama-instruct
```
## Quantized GGUF Models
| Name | Quant method | Bits | Size | Use case |
| ---- | ---- | ---- | ---- | ----- |
| [CodeLlama-13b-Instruct-hf-Q2_K.gguf](https://huggingface.co/second-state/CodeLlama-13B-Instruct-GGUF/blob/main/CodeLlama-13b-Instruct-hf-Q2_K.gguf) | Q2_K | 2 | 5.43 GB| smallest, significant quality loss - not recommended for most purposes |
| [CodeLlama-13b-Instruct-hf-Q3_K_L.gguf](https://huggingface.co/second-state/CodeLlama-13B-Instruct-GGUF/blob/main/CodeLlama-13b-Instruct-hf-Q3_K_L.gguf) | Q3_K_L | 3 | 6.93 GB| small, substantial quality loss |
| [CodeLlama-13b-Instruct-hf-Q3_K_M.gguf](https://huggingface.co/second-state/CodeLlama-13B-Instruct-GGUF/blob/main/CodeLlama-13b-Instruct-hf-Q3_K_M.gguf) | Q3_K_M | 3 | 6.34 GB| very small, high quality loss |
| [CodeLlama-13b-Instruct-hf-Q3_K_S.gguf](https://huggingface.co/second-state/CodeLlama-13B-Instruct-GGUF/blob/main/CodeLlama-13b-Instruct-hf-Q3_K_S.gguf) | Q3_K_S | 3 | 5.66 GB| very small, high quality loss |
| [CodeLlama-13b-Instruct-hf-Q4_0.gguf](https://huggingface.co/second-state/CodeLlama-13B-Instruct-GGUF/blob/main/CodeLlama-13b-Instruct-hf-Q4_0.gguf) | Q4_0 | 4 | 7.37 GB| legacy; small, very high quality loss - prefer using Q3_K_M |
| [CodeLlama-13b-Instruct-hf-Q4_K_M.gguf](https://huggingface.co/second-state/CodeLlama-13B-Instruct-GGUF/blob/main/CodeLlama-13b-Instruct-hf-Q4_K_M.gguf) | Q4_K_M | 4 | 7.87 GB| medium, balanced quality - recommended |
| [CodeLlama-13b-Instruct-hf-Q4_K_S.gguf](https://huggingface.co/second-state/CodeLlama-13B-Instruct-GGUF/blob/main/CodeLlama-13b-Instruct-hf-Q4_K_S.gguf) | Q4_K_S | 4 | 7.41 GB| small, greater quality loss |
| [CodeLlama-13b-Instruct-hf-Q5_0.gguf](https://huggingface.co/second-state/CodeLlama-13B-Instruct-GGUF/blob/main/CodeLlama-13b-Instruct-hf-Q5_0.gguf) | Q5_0 | 5 | 8.97 GB| legacy; medium, balanced quality - prefer using Q4_K_M |
| [CodeLlama-13b-Instruct-hf-Q5_K_M.gguf](https://huggingface.co/second-state/CodeLlama-13B-Instruct-GGUF/blob/main/CodeLlama-13b-Instruct-hf-Q5_K_M.gguf) | Q5_K_M | 5 | 9.23 GB| large, very low quality loss - recommended |
| [CodeLlama-13b-Instruct-hf-Q5_K_S.gguf](https://huggingface.co/second-state/CodeLlama-13B-Instruct-GGUF/blob/main/CodeLlama-13b-Instruct-hf-Q5_K_S.gguf) | Q5_K_S | 5 | 8.97 GB| large, low quality loss - recommended |
| [CodeLlama-13b-Instruct-hf-Q6_K.gguf](https://huggingface.co/second-state/CodeLlama-13B-Instruct-GGUF/blob/main/CodeLlama-13b-Instruct-hf-Q6_K.gguf) | Q6_K | 6 | 10.7 GB| very large, extremely low quality loss |
| [CodeLlama-13b-Instruct-hf-Q8_0.gguf](https://huggingface.co/second-state/CodeLlama-13B-Instruct-GGUF/blob/main/CodeLlama-13b-Instruct-hf-Q8_0.gguf) | Q8_0 | 8 | 13.8 GB| very large, extremely low quality loss - not recommended |

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{
"architectures": [
"LlamaForCausalLM"
],
"bos_token_id": 1,
"eos_token_id": 2,
"hidden_act": "silu",
"hidden_size": 5120,
"initializer_range": 0.02,
"intermediate_size": 13824,
"max_position_embeddings": 16384,
"model_type": "llama",
"num_attention_heads": 40,
"num_hidden_layers": 40,
"num_key_value_heads": 40,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 1000000,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.32.0.dev0",
"use_cache": true,
"vocab_size": 32016
}

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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}