base_model: yuuko-eth/Chihiro-7B-v0.1
language:
- zh
- en
library_name: transformers
license: unknown
model_name: Chihiro-7B-v0.1
prompt_template: <s> SYS_PROMPT [INST] QUERY1 [/INST] RESPONSE1 [INST] QUERY2 [/INST]
quantized_by: mradermacher
tags:
- nlp
- chinese
- mistral
- traditional_chinese
- merge
- mergekit
- MediaTek-Research/Breeze-7B-Instruct-v0_1
- mlabonne/Zebrafish-7B
About
static quants of https://huggingface.co/yuuko-eth/Chihiro-7B-v0.1
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Chihiro-7B-v0.1-i1-GGUF
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 | 3.0 | |
| GGUF | Q3_K_S | 3.4 | |
| GGUF | Q3_K_M | 3.8 | lower quality |
| GGUF | Q3_K_L | 4.1 | |
| GGUF | IQ4_XS | 4.2 | |
| GGUF | Q4_K_S | 4.4 | fast, recommended |
| GGUF | Q4_K_M | 4.6 | fast, recommended |
| GGUF | Q5_K_S | 5.3 | |
| GGUF | Q5_K_M | 5.4 | |
| GGUF | Q6_K | 6.2 | very good quality |
| GGUF | Q8_0 | 8.1 | fast, best quality |
| GGUF | f16 | 15.1 | 16 bpw, overkill |
Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):
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.