metadata
base_model: baichuan-inc/Baichuan2-13B-Chat
inference: false
library_name: transformers
license: other
model_creator: Baichuan Intelligent Technology
model_name: Baichuan2 13B Chat
model_type: baichuan
tasks:
- text-generation
quantized_by: Second State Inc.
language:
- en
- zh
Baichuan2-13B-Chat-GGUF
Original Model
baichuan-inc/Baichuan2-13B-Chat
Run with LlamaEdge
LlamaEdge version: v0.2.8 and above
Prompt template
Prompt type:
baichuan-2
Prompt string
以下内容为人类用户与与一位智能助手的对话。 用户:你好! 助手:
Reverse prompt:
用户:
Run as LlamaEdge service
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Baichuan2-13B-Chat-Q5_K_M.gguf llama-api-server.wasm -p baichuan-2 -r '用户:'
Run as LlamaEdge command app
wasmedge --dir .:. --nn-preload default:GGML:AUTO:Baichuan2-13B-Chat-Q5_K_M.gguf llama-chat.wasm -p baichuan-2 -r '用户:'
Quantized GGUF Models
Name | Quant method | Bits | Size | Use case |
---|---|---|---|---|
Baichuan2-13B-Chat-Q2_K.gguf | Q2_K | 2 | 6.5 GB | smallest, significant quality loss - not recommended for most purposes |
Baichuan2-13B-Chat-Q3_K_L.gguf | Q3_K_L | 3 | 7.67 GB | small, substantial quality loss |
Baichuan2-13B-Chat-Q3_K_M.gguf | Q3_K_M | 3 | 7.24 GB | very small, high quality loss |
Baichuan2-13B-Chat-Q3_K_S.gguf | Q3_K_S | 3 | 6.77 GB | very small, high quality loss |
Baichuan2-13B-Chat-Q4_0.gguf | Q4_0 | 4 | 7.99 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
Baichuan2-13B-Chat-Q4_K_M.gguf | Q4_K_M | 4 | 9.00 GB | medium, balanced quality - recommended |
Baichuan2-13B-Chat-Q4_K_S.gguf | Q4_K_S | 4 | 8.37 GB | small, greater quality loss |
Baichuan2-13B-Chat-Q5_0.gguf | Q5_0 | 5 | 9.64 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
Baichuan2-13B-Chat-Q5_K_M.gguf | Q5_K_M | 5 | 10.3 GB | large, very low quality loss - recommended |
Baichuan2-13B-Chat-Q5_K_S.gguf | Q5_K_S | 5 | 9.82 GB | large, low quality loss - recommended |
Baichuan2-13B-Chat-Q6_K.gguf | Q6_K | 6 | 12.1 GB | very large, extremely low quality loss |
Baichuan2-13B-Chat-Q8_0.gguf | Q8_0 | 8 | 14.8 GB | very large, extremely low quality loss - not recommended |