Transformers
GGUF
multilingual
sea
sailor
sft
chat
instruction
Inference Endpoints
conversational
mradermacher's picture
auto-patch README.md
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metadata
base_model: sail/Sailor-0.5B-Chat
datasets:
  - CohereForAI/aya_dataset
  - CohereForAI/aya_collection
  - Open-Orca/OpenOrca
language:
  - en
  - zh
  - id
  - th
  - vi
  - ms
  - lo
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
  - multilingual
  - sea
  - sailor
  - sft
  - chat
  - instruction

About

static quants of https://huggingface.co/sail/Sailor-0.5B-Chat

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
GGUF Q2_K 0.4
GGUF IQ3_XS 0.4
GGUF IQ3_S 0.4 beats Q3_K*
GGUF Q3_K_S 0.4
GGUF IQ3_M 0.4
GGUF Q3_K_M 0.4 lower quality
GGUF Q3_K_L 0.5
GGUF IQ4_XS 0.5
GGUF Q4_K_S 0.5 fast, recommended
GGUF Q4_K_M 0.5 fast, recommended
GGUF Q5_K_S 0.6
GGUF Q5_K_M 0.6
GGUF Q6_K 0.6 very good quality
GGUF Q8_0 0.8 fast, best quality
GGUF f16 1.3 16 bpw, overkill

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.png

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.