metadata

language:
  - en
license: llama2
tags:
  - facebook
  - meta
  - pytorch
  - llama
  - llama-2
model_name: Llama 2 7B Chat
arxiv: 2307.09288
base_model: meta-llama/Llama-2-7b-chat-hf
inference: false
model_creator: Meta Llama 2
model_type: llama
pipeline_tag: text-generation
quantized_by: Second State Inc.

Llama-2-7B-Chat-GGUF

Original Model

meta-llama/Llama-2-7b-chat-hf

Run with LlamaEdge

LlamaEdge version: v0.2.8 and above

Prompt template

Prompt type: llama-2-chat

Prompt string

<s>[INST] <<SYS>>
{{ system_prompt }}
<</SYS>>

{{ user_msg_1 }} [/INST] {{ model_answer_1 }} </s><s>[INST] {{ user_msg_2 }}   [/INST]

Context size: 4096

Run as LlamaEdge service

wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-2-7b-chat-hf-Q5_K_M.gguf llama-api-server.wasm -p llama-2-chat

Run as LlamaEdge command app

wasmedge --dir .:. --nn-preload default:GGML:AUTO:Llama-2-7b-chat-hf-Q5_K_M.gguf llama-chat.wasm -p llama-2-chat

Quantized GGUF Models

Name	Quant method	Bits	Size	Use case
Llama-2-7b-chat-hf-Q2_K.gguf	Q2_K	2	2.83 GB	smallest, significant quality loss - not recommended for most purposes
Llama-2-7b-chat-hf-Q3_K_L.gguf	Q3_K_L	3	3.6 GB	small, substantial quality loss
Llama-2-7b-chat-hf-Q3_K_M.gguf	Q3_K_M	3	3.3 GB	very small, high quality loss
Llama-2-7b-chat-hf-Q3_K_S.gguf	Q3_K_S	3	2.95 GB	very small, high quality loss
Llama-2-7b-chat-hf-Q4_0.gguf	Q4_0	4	3.83 GB	legacy; small, very high quality loss - prefer using Q3_K_M
Llama-2-7b-chat-hf-Q4_K_M.gguf	Q4_K_M	4	4.08 GB	medium, balanced quality - recommended
Llama-2-7b-chat-hf-Q4_K_S.gguf	Q4_K_S	4	3.86 GB	small, greater quality loss
Llama-2-7b-chat-hf-Q5_0.gguf	Q5_0	5	4.65 GB	legacy; medium, balanced quality - prefer using Q4_K_M
Llama-2-7b-chat-hf-Q5_K_M.gguf	Q5_K_M	5	4.78 GB	large, very low quality loss - recommended
Llama-2-7b-chat-hf-Q5_K_S.gguf	Q5_K_S	5	4.65 GB	large, low quality loss - recommended
Llama-2-7b-chat-hf-Q6_K.gguf	Q6_K	6	5.53 GB	very large, extremely low quality loss
Llama-2-7b-chat-hf-Q8_0.gguf	Q8_0	8	7.16 GB	very large, extremely low quality loss - not recommended