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mradermacher/falcon-180B-WizardLM_Orca-GGUF
falcon-180B-WizardLM_Orca-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.
static quants of https://huggingface.co/quantumaikr/falcon-180B-WizardLMOrca
Downloads · 30 days
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Updated Dec 16, 2024
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.part1of2326 GB · 18%
From the Hugging Face model README
static quants of https://huggingface.co/quantumaikr/falcon-180B-WizardLM_Orca
<!-- provided-files -->weighted/imatrix quants are available at https://huggingface.co/mradermacher/falcon-180B-WizardLM_Orca-i1-GGUF
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.
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
| Link | Type | Size/GB | Notes |
|---|---|---|---|
| PART 1 PART 2 | Q2_K | 65.9 | |
| PART 1 PART 2 | IQ3_XS | 74.4 | |
| PART 1 PART 2 | IQ3_S | 76.8 | beats Q3_K* |
| PART 1 PART 2 | Q3_K_S | 76.8 | |
| PART 1 PART 2 | IQ3_M | 80.5 | |
| PART 1 PART 2 | Q3_K_M | 84.6 | lower quality |
| PART 1 PART 2 | Q3_K_L | 91.1 | |
| PART 1 PART 2 | IQ4_XS | 96.4 | |
| PART 1 PART 2 PART 3 | Q4_K_S | 100.6 | fast, recommended |
| PART 1 PART 2 PART 3 | Q4_K_M | 107.9 | fast, recommended |
| PART 1 PART 2 PART 3 | Q5_K_S | 122.9 | |
| PART 1 PART 2 PART 3 | Q5_K_M | 130.1 | |
| PART 1 PART 2 PART 3 PART 4 | Q6_K | 146.6 | very good quality |
| PART 1 PART 2 PART 3 PART 4 | Q8_0 | 189.8 | fast, best quality |
| P1 P2 P3 P4 P5 P6 P7 P8 | SOURCE | 357.2 | source gguf, only provided when it was hard to come by |
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
See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.
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.
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