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metadata
base_model: PipableAI/pip-library-etl-1.3b
language:
  - en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
  - python
  - java
  - cpp
  - sql
  - function calling
  - unit tests
  - causalLM
  - codeLLAMA modified archi
  - document
  - code
  - code2doc
  - instruction_tuned
  - basemodel
  - pytorch
  - docstring
  - documentation
  - text-generation-inference

About

static quants of https://huggingface.co/PipableAI/pip-library-etl-1.3b

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 0.7
GGUF Q3_K_S 0.7
GGUF Q3_K_M 0.8 lower quality
GGUF Q3_K_L 0.8
GGUF IQ4_XS 0.9
GGUF Q4_K_S 0.9 fast, recommended
GGUF Q4_K_M 1.0 fast, recommended
GGUF Q5_K_S 1.1
GGUF Q5_K_M 1.1
GGUF Q6_K 1.3 very good quality
GGUF Q8_0 1.5 fast, best quality
GGUF f16 2.8 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. 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.