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Model: second-state/Llama-3.2-3B-Instruct-GGUF
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---
base_model: meta-llama/Llama-3.2-3B-Instruct
license: llama3.2
model_creator: meta
model_name: Llama-3.2-3B-Instruct
quantized_by: Second State Inc.
language:
- en
- de
- fr
- it
- pt
- hi
- es
- th
library_name: transformers
pipeline_tag: text-generation
tags:
- chat
- llama
- llama-3
---
<!-- 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 -->
# Llama-3.2-3B-Instruct-GGUF
## Original Model
[meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct)
## Run with LlamaEdge
- LlamaEdge version: [v0.16.5](https://github.com/LlamaEdge/LlamaEdge/releases/tag/0.16.5) and above
- Prompt template
- Prompt type for chat: `llama-3-chat`
- Prompt string
```text
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
{{ system_prompt }}<|eot_id|><|start_header_id|>user<|end_header_id|>
{{ user_message_1 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
{{ model_answer_1 }}<|eot_id|><|start_header_id|>user<|end_header_id|>
{{ user_message_2 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
```
- Prompt type for tool use: `llama-3-tool`
- Prompt string
```text
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
{system_message}<|eot_id|><|start_header_id|>user<|end_header_id|>
Given the following functions, please respond with a JSON for a function call with its proper arguments that best answers the given prompt.
Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}. Do not use variables.
[{"type":"function","function":{"name":"get_current_weather","description":"Get the current weather in a given location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The city and state, e.g. San Francisco, CA"},"unit":{"type":"string","description":"The temperature unit to use. Infer this from the users location.","enum":["celsius","fahrenheit"]}},"required":["location","unit"]}}}]
Question: {user_message}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
```
- Context size: `128000`
- Run as LlamaEdge service
- Chat
```bash
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3.2-3B-Instruct-Q5_K_M.gguf \
llama-api-server.wasm \
--prompt-template llama-3-chat \
--ctx-size 128000 \
--model-name Llama-3.2-3b
```
- Tool use
```bash
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3.2-3B-Instruct-Q5_K_M.gguf \
llama-api-server.wasm \
--prompt-template llama-3-tool \
--ctx-size 128000 \
--model-name Llama-3.2-3b
```
- Run as LlamaEdge command app
```bash
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3.2-3B-Instruct-Q5_K_M.gguf \
llama-chat.wasm \
--prompt-template llama-3-chat \
--ctx-size 128000
```
## Quantized GGUF Models
| Name | Quant method | Bits | Size | Use case |
| ---- | ---- | ---- | ---- | ----- |
| [Llama-3.2-3B-Instruct-Q2_K.gguf](https://huggingface.co/second-state/Llama-3.2-3B-Instruct-GGUF/blob/main/Llama-3.2-3B-Instruct-Q2_K.gguf) | Q2_K | 2 | 581 MB| smallest, significant quality loss - not recommended for most purposes |
| [Llama-3.2-3B-Instruct-Q3_K_L.gguf](https://huggingface.co/second-state/Llama-3.2-3B-Instruct-GGUF/blob/main/Llama-3.2-3B-Instruct-Q3_K_L.gguf) | Q3_K_L | 3 | 733 MB| small, substantial quality loss |
| [Llama-3.2-3B-Instruct-Q3_K_M.gguf](https://huggingface.co/second-state/Llama-3.2-3B-Instruct-GGUF/blob/main/Llama-3.2-3B-Instruct-Q3_K_M.gguf) | Q3_K_M | 3 | 691 MB| very small, high quality loss |
| [Llama-3.2-3B-Instruct-Q3_K_S.gguf](https://huggingface.co/second-state/Llama-3.2-3B-Instruct-GGUF/blob/main/Llama-3.2-3B-Instruct-Q3_K_S.gguf) | Q3_K_S | 3 | 642 MB| very small, high quality loss |
| [Llama-3.2-3B-Instruct-Q4_0.gguf](https://huggingface.co/second-state/Llama-3.2-3B-Instruct-GGUF/blob/main/Llama-3.2-3B-Instruct-Q4_0.gguf) | Q4_0 | 4 | 771 MB| legacy; small, very high quality loss - prefer using Q3_K_M |
| [Llama-3.2-3B-Instruct-Q4_K_M.gguf](https://huggingface.co/second-state/Llama-3.2-3B-Instruct-GGUF/blob/main/Llama-3.2-3B-Instruct-Q4_K_M.gguf) | Q4_K_M | 4 | 808 MB| medium, balanced quality - recommended |
| [Llama-3.2-3B-Instruct-Q4_K_S.gguf](https://huggingface.co/second-state/Llama-3.2-3B-Instruct-GGUF/blob/main/Llama-3.2-3B-Instruct-Q4_K_S.gguf) | Q4_K_S | 4 | 776 MB| small, greater quality loss |
| [Llama-3.2-3B-Instruct-Q5_0.gguf](https://huggingface.co/second-state/Llama-3.2-3B-Instruct-GGUF/blob/main/Llama-3.2-3B-Instruct-Q5_0.gguf) | Q5_0 | 5 | 893 MB| legacy; medium, balanced quality - prefer using Q4_K_M |
| [Llama-3.2-3B-Instruct-Q5_K_M.gguf](https://huggingface.co/second-state/Llama-3.2-3B-Instruct-GGUF/blob/main/Llama-3.2-3B-Instruct-Q5_K_M.gguf) | Q5_K_M | 5 | 912 MB| large, very low quality loss - recommended |
| [Llama-3.2-3B-Instruct-Q5_K_S.gguf](https://huggingface.co/second-state/Llama-3.2-3B-Instruct-GGUF/blob/main/Llama-3.2-3B-Instruct-Q5_K_S.gguf) | Q5_K_S | 5 | 893 MB| large, low quality loss - recommended |
| [Llama-3.2-3B-Instruct-Q6_K.gguf](https://huggingface.co/second-state/Llama-3.2-3B-Instruct-GGUF/blob/main/Llama-3.2-3B-Instruct-Q6_K.gguf) | Q6_K | 6 | 1.02 GB| very large, extremely low quality loss |
| [Llama-3.2-3B-Instruct-Q8_0.gguf](https://huggingface.co/second-state/Llama-3.2-3B-Instruct-GGUF/blob/main/Llama-3.2-3B-Instruct-Q8_0.gguf) | Q8_0 | 8 | 1.32 GB| very large, extremely low quality loss - not recommended |
| [Llama-3.2-3B-Instruct-f16.gguf](https://huggingface.co/second-state/Llama-3.2-3B-Instruct-GGUF/blob/main/Llama-3.2-3B-Instruct-f16.gguf) | f16 | 16 | 2.48 GB| |
*Quantized with llama.cpp b4466*

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{
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"eos_token_id": [
128001,
128008,
128009
],
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 3072,
"initializer_range": 0.02,
"intermediate_size": 8192,
"max_position_embeddings": 131072,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 24,
"num_hidden_layers": 28,
"num_key_value_heads": 8,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": {
"factor": 32.0,
"high_freq_factor": 4.0,
"low_freq_factor": 1.0,
"original_max_position_embeddings": 8192,
"rope_type": "llama3"
},
"rope_theta": 500000.0,
"tie_word_embeddings": true,
"torch_dtype": "bfloat16",
"transformers_version": "4.45.0.dev0",
"use_cache": true,
"vocab_size": 128256
}

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