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Tor-8B-i1-GGUF
mradermacher/Tor-8B-i1-GGUF
Tor-8B-i1-GGUF is a machine learning model from mradermacher. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as agpl-3.0.
weighted/imatrix quants of https://huggingface.co/Delta-Vector/Tor-8B
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Repo size
99.5 GB
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.gguf99.5 GB · 100%
At a glance
- Library
- transformers
- License
- agpl-3.0
- Access
- Public
- Created
- Dec 3, 2024
- Updated
- Dec 3, 2024
- SHA
- db86dd76
Base models
Datasets
- anthracite-org/c2_logs_16k_llama_v1.1
- anthracite-org/kalo-opus-instruct-22k-no-refusal
- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
- lodrick-the-lafted/kalo-opus-instruct-3k-filtered
- anthracite-org/nopm_claude_writing_fixed
- Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
- anthracite-org/kalo_opus_misc_240827
- anthracite-org/kalo_misc_part2
Model card
From the Hugging Face model README
About
<!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: nicoboss -->weighted/imatrix quants of https://huggingface.co/Delta-Vector/Tor-8B
<!-- provided-files -->static quants are available at https://huggingface.co/mradermacher/Tor-8B-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_S | 2.2 | for the desperate |
| GGUF | i1-IQ1_M | 2.4 | mostly desperate |
| GGUF | i1-IQ2_XXS | 2.6 | |
| GGUF | i1-IQ2_XS | 2.8 | |
| GGUF | i1-IQ2_S | 3.0 | |
| GGUF | i1-IQ2_M | 3.2 | |
| GGUF | i1-Q2_K | 3.4 | IQ3_XXS probably better |
| GGUF | i1-IQ3_XXS | 3.5 | lower quality |
| GGUF | i1-IQ3_XS | 3.8 | |
| GGUF | i1-Q3_K_S | 3.9 | IQ3_XS probably better |
| GGUF | i1-IQ3_S | 4.0 | beats Q3_K* |
| GGUF | i1-IQ3_M | 4.1 | |
| GGUF | i1-Q3_K_M | 4.3 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 4.6 | IQ3_M probably better |
| GGUF | i1-IQ4_XS | 4.8 | |
| GGUF | i1-Q4_0_4_4 | 5.0 | fast on arm, low quality |
| GGUF | i1-Q4_0_4_8 | 5.0 | fast on arm+i8mm, low quality |
| GGUF | i1-Q4_0_8_8 | 5.0 | fast on arm+sve, low quality |
| GGUF | i1-Q4_0 | 5.0 | fast, low quality |
| GGUF | i1-Q4_K_S | 5.0 | optimal size/speed/quality |
| GGUF | i1-Q4_K_M | 5.2 | fast, recommended |
| GGUF | i1-Q5_K_S | 6.0 | |
| GGUF | i1-Q5_K_M | 6.1 | |
| GGUF | i1-Q6_K | 7.0 | practically like static Q6_K |
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. 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.
<!-- end -->- Library
- transformers
- License
- agpl-3.0
- Languages
- en
- Created
- Dec 3, 2024
- Updated
- Dec 3, 2024