Edit model card

Codestral-22B-v0.1-GGUF

Original Model

mistralai/Codestral-22B-v0.1

Run with Gaianet

Prompt template

prompt template: mistral-instruct

Context size

chat_ctx_size: 32000

Run with GaiaNet

Quantized GGUF Models

Name Quant method Bits Size Use case
Codestral-22B-v0.1-hf-Q2_K.gguf Q2_K 2 8.27 GB smallest, significant quality loss - not recommended for most purposes
Codestral-22B-v0.1-hf-Q3_K_L.gguf Q3_K_L 3 11.7 GB small, substantial quality loss
Codestral-22B-v0.1-hf-Q3_K_M.gguf Q3_K_M 3 10.8 GB very small, high quality loss
Codestral-22B-v0.1-hf-Q3_K_S.gguf Q3_K_S 3 9.64 GB very small, high quality loss
Codestral-22B-v0.1-hf-Q4_0.gguf Q4_0 4 12.6 GB legacy; small, very high quality loss - prefer using Q3_K_M
Codestral-22B-v0.1-hf-Q4_K_M.gguf Q4_K_M 4 13.3 GB medium, balanced quality - recommended
Codestral-22B-v0.1-hf-Q4_K_S.gguf Q4_K_S 4 12.7 GB small, greater quality loss
Codestral-22B-v0.1-hf-Q5_0.gguf Q5_0 5 15.3 GB legacy; medium, balanced quality - prefer using Q4_K_M
Codestral-22B-v0.1-hf-Q5_K_M.gguf Q5_K_M 5 15.7 GB large, very low quality loss - recommended
Codestral-22B-v0.1-hf-Q5_K_S.gguf Q5_K_S 5 15.3 GB large, low quality loss - recommended
Codestral-22B-v0.1-hf-Q6_K.gguf Q6_K 6 18.3 GB very large, extremely low quality loss
Codestral-22B-v0.1-hf-Q8_0.gguf Q8_0 8 23.6 GB very large, extremely low quality loss - not recommended
Codestral-22B-v0.1-hf-f16.gguf f16 16 44.5 GB

Quantized with llama.cpp b3030.

Downloads last month
91
GGUF
Model size
22.2B params
Architecture
llama

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Inference Examples
Inference API (serverless) has been turned off for this model.

Model tree for gaianet/Codestral-22B-v0.1-GGUF

Quantized
(27)
this model