metadata
base_model: unsloth/Devstral-Small-2505
language:
- en
- fr
- de
- es
- pt
- it
- ja
- ko
- ru
- zh
- ar
- fa
- id
- ms
- ne
- pl
- ro
- sr
- sv
- tr
- uk
- vi
- hi
- bn
library_name: vllm
license: apache-2.0
pipeline_tag: text2text-generation
tags:
- llama-cpp
- gguf-my-repo
inference: false
extra_gated_description: >-
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Produced by Antigma Labs, Antigma Quantize Space
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llama.cpp quantization
Using llama.cpp release b5223 for quantization. Original model: https://huggingface.co/unsloth/Devstral-Small-2505 Run them directly with llama.cpp, or any other llama.cpp based project
Prompt format
<｜begin▁of▁sentence｜>{system_prompt}<｜User｜>{prompt}<｜Assistant｜><｜end▁of▁sentence｜><｜Assistant｜>
Download a file (not the whole branch) from below:
| Filename | Quant type | File Size | Split |
|---|---|---|---|
| devstral-small-2505-q2_k.gguf | Q2_K | 8.28 GB | False |
| devstral-small-2505-q3_k_l.gguf | Q3_K_L | 11.55 GB | False |
| devstral-small-2505-q6_k.gguf | Q6_K | 18.02 GB | False |
| devstral-small-2505-q4_k_m.gguf | Q4_K_M | 13.35 GB | False |
| devstral-small-2505-q5_k_m.gguf | Q5_K_M | 15.61 GB | False |
| devstral-small-2505-q8_0.gguf | Q8_0 | 23.33 GB | False |
Downloading using huggingface-cli
Click to view download instructions
First, make sure you have hugginface-cli installed:pip install -U "huggingface_hub[cli]"
Then, you can target the specific file you want:
huggingface-cli download https://huggingface.co/Antigma/Devstral-Small-2505-GGUF --include "devstral-small-2505-q2_k.gguf" --local-dir ./
If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:
huggingface-cli download https://huggingface.co/Antigma/Devstral-Small-2505-GGUF --include "devstral-small-2505-q2_k.gguf/*" --local-dir ./
You can either specify a new local-dir (deepseek-ai_DeepSeek-V3-0324-Q8_0) or download them all in place (./)