base_model, language, library_name, license, license_link, license_name, model_type, quantized_by, tags

base_model	language	library_name	license	license_link	license_name	model_type	quantized_by	tags
ValiantLabs/Fireplace-34b	en	transformers	other	https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE	yi-license	llama	mradermacher	fireplace function-calling code code-instruct conversational text-generation-inference valiant valiant-labs smaug yi yi-34b llama llama-2 llama-2-chat 34b

About

static quants of https://huggingface.co/ValiantLabs/Fireplace-34b

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	14.4
GGUF	IQ3_XS	15.8
GGUF	Q3_K_S	16.5
GGUF	IQ3_S	16.6	beats Q3_K*
GGUF	IQ3_M	17.1
GGUF	Q3_K_M	18.2	lower quality
GGUF	Q3_K_L	19.7
GGUF	IQ4_XS	20.2
GGUF	Q4_K_S	21.2	fast, recommended
GGUF	Q4_K_M	22.2	fast, recommended
GGUF	Q5_K_S	25.3
GGUF	Q5_K_M	25.9
GGUF	Q6_K	29.8	very good quality
GGUF	Q8_0	38.0	fast, best quality

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.