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stablelm-2-12b-chat-i1-GGUF

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metadata
base_model: stabilityai/stablelm-2-12b-chat
datasets:
  - HuggingFaceH4/ultrachat_200k
  - allenai/ultrafeedback_binarized_cleaned
  - meta-math/MetaMathQA
  - WizardLM/WizardLM_evol_instruct_V2_196k
  - openchat/openchat_sharegpt4_dataset
  - LDJnr/Capybara
  - Intel/orca_dpo_pairs
  - hkust-nlp/deita-10k-v0
  - Anthropic/hh-rlhf
  - glaiveai/glaive-function-calling-v2
extra_gated_fields:
  Country: text
  Email: text
  I ALLOW Stability AI to email me about new model releases: checkbox
  Name: text
  Organization or Affiliation: text
language:
  - en
library_name: transformers
license: other
quantized_by: mradermacher
tags:
  - causal-lm

About

weighted/imatrix quants of https://huggingface.co/stabilityai/stablelm-2-12b-chat

static quants are available at https://huggingface.co/mradermacher/stablelm-2-12b-chat-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 i1-IQ1_M 3.2 mostly desperate
GGUF i1-IQ2_XXS 3.6
GGUF i1-IQ2_M 4.5
GGUF i1-Q2_K_S 4.5 very low quality
GGUF i1-Q2_K 4.8 IQ3_XXS probably better
GGUF i1-IQ3_XXS 4.9 lower quality
GGUF i1-Q3_K_S 5.5 IQ3_XS probably better
GGUF i1-IQ3_M 5.7
GGUF i1-Q3_K_M 6.1 IQ3_S probably better
GGUF i1-Q3_K_L 6.6 IQ3_M probably better
GGUF i1-IQ4_XS 6.7
GGUF i1-Q4_K_S 7.1 optimal size/speed/quality
GGUF i1-Q4_K_M 7.5 fast, recommended
GGUF i1-Q6_K 10.1 practically like static Q6_K

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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.