mradermacher/Llama-PLLuM-70B-instruct-GGUF overview
About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: static quants of https://huggingface.co/CYFRAGOVPL/Llama PLLu…
Runs locally from ~24.56 GB disk (32 GB+ VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Llama-PLLuM-70B-instruct.IQ4_XS.gguf | GGUF | GGUF | 35.64 GB | Download |
| Llama-PLLuM-70B-instruct.Q2_K.gguf | GGUF | GGUF | 24.56 GB | Download |
| Llama-PLLuM-70B-instruct.Q3_K_L.gguf | GGUF | GGUF | 34.59 GB | Download |
| Llama-PLLuM-70B-instruct.Q3_K_M.gguf | GGUF | GGUF | 31.91 GB | Download |
| Llama-PLLuM-70B-instruct.Q3_K_S.gguf | GGUF | GGUF | 28.79 GB | Download |
| Llama-PLLuM-70B-instruct.Q4_K_M.gguf | GGUF | GGUF | 39.60 GB | Download |
| Llama-PLLuM-70B-instruct.Q4_K_S.gguf | GGUF | GGUF | 37.58 GB | Download |
| Llama-PLLuM-70B-instruct.Q5_K_M.gguf | GGUF | GGUF | 46.52 GB | Download |
| Llama-PLLuM-70B-instruct.Q5_K_S.gguf | GGUF | GGUF | 45.32 GB | Download |
Model Details
| Model ID | mradermacher/Llama-PLLuM-70B-instruct-GGUF |
|---|---|
| Author | mradermacher |
| Pipeline | — |
| License | llama3.1 |
| Base model | CYFRAGOVPL/Llama-PLLuM-70B-instruct-2412 |
| Last modified | 2026-07-25T22:37:28.000Z |
Model README
---
base_model: CYFRAGOVPL/Llama-PLLuM-70B-instruct-2412
language:
- pl
library_name: transformers
license: llama3.1
mradermacher:
readme_rev: 1
quantized_by: mradermacher
---
About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
static quants of https://huggingface.co/CYFRAGOVPL/Llama-PLLuM-70B-instruct-2412
<!-- provided-files -->
For a convenient overview and download list, visit our model page for this model.
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](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) 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 | 26.5 | |
| GGUF | Q3_K_S | 31.0 | |
| GGUF | Q3_K_M | 34.4 | lower quality |
| GGUF | Q3_K_L | 37.2 | |
| GGUF | IQ4_XS | 38.4 | |
| GGUF | Q4_K_S | 40.4 | fast, recommended |
| GGUF | Q4_K_M | 42.6 | fast, recommended |
| GGUF | Q5_K_S | 48.8 | |
| GGUF | Q5_K_M | 50.0 | |
| PART 1 PART 2 | Q6_K | 58.0 | very good quality |
| PART 1 PART 2 | Q8_0 | 75.1 | 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.
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