base_model: thirdeyeai/Llama-3.2-3B-Instruct-Uncensored
model_creator: thirdeyeai
model_name: Llama-3.2-3B-Instruct-Uncensored
quantized_by: Second State Inc.
library_name: transformers
Llama-3.2-3B-Instruct-Uncensored-GGUF
Original Model
thirdeyeai/Llama-3.2-3B-Instruct-Uncensored
Run with LlamaEdge
LlamaEdge version: v0.16.8 and above
Prompt template
Prompt type for chat:
llama-3-chatPrompt string
<|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-toolPrompt string
<|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:
128000Run as LlamaEdge service
Chat
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3.2-3B-Instruct-Uncensored-Q5_K_M.gguf \ llama-api-server.wasm \ --prompt-template llama-3-chat \ --ctx-size 128000 \ --model-name Llama-3.2-3bTool use
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3.2-3B-Instruct-Uncensored-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
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-3.2-3B-Instruct-Uncensored-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-Uncensored-Q2_K.gguf | Q2_K | 2 | 1.49 GB | smallest, significant quality loss - not recommended for most purposes |
| Llama-3.2-3B-Instruct-Uncensored-Q3_K_L.gguf | Q3_K_L | 3 | 1.98 GB | small, substantial quality loss |
| Llama-3.2-3B-Instruct-Uncensored-Q3_K_M.gguf | Q3_K_M | 3 | 1.86 GB | very small, high quality loss |
| Llama-3.2-3B-Instruct-Uncensored-Q3_K_S.gguf | Q3_K_S | 3 | 1.71 GB | very small, high quality loss |
| Llama-3.2-3B-Instruct-Uncensored-Q4_0.gguf | Q4_0 | 4 | 2.14 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Llama-3.2-3B-Instruct-Uncensored-Q4_K_M.gguf | Q4_K_M | 4 | 2.24 GB | medium, balanced quality - recommended |
| Llama-3.2-3B-Instruct-Uncensored-Q4_K_S.gguf | Q4_K_S | 4 | 2.15 GB | small, greater quality loss |
| Llama-3.2-3B-Instruct-Uncensored-Q5_0.gguf | Q5_0 | 5 | 2.54 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Llama-3.2-3B-Instruct-Uncensored-Q5_K_M.gguf | Q5_K_M | 5 | 2.59 GB | large, very low quality loss - recommended |
| Llama-3.2-3B-Instruct-Uncensored-Q5_K_S.gguf | Q5_K_S | 5 | 2.54 GB | large, low quality loss - recommended |
| Llama-3.2-3B-Instruct-Uncensored-Q6_K.gguf | Q6_K | 6 | 2.97 GB | very large, extremely low quality loss |
| Llama-3.2-3B-Instruct-Uncensored-Q8_0.gguf | Q8_0 | 8 | 3.84 GB | very large, extremely low quality loss - not recommended |
| Llama-3.2-3B-Instruct-Uncensored-f16.gguf | f16 | 16 | 7.22 GB |
Quantized with llama.cpp b4681