--- base_model: EVA-UNIT-01/EVA-Qwen2.5-72B-v0.0 datasets: - anthracite-org/kalo-opus-instruct-22k-no-refusal - Nopm/Opus_WritingStruct - Gryphe/Sonnet3.5-SlimOrcaDedupCleaned - Gryphe/Sonnet3.5-Charcard-Roleplay - Gryphe/ChatGPT-4o-Writing-Prompts - Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned - Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned - nothingiisreal/Reddit-Dirty-And-WritingPrompts - allura-org/Celeste-1.x-data-mixture language: - en library_name: transformers license: other license_link: https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE license_name: qwen quantized_by: mradermacher tags: - generated_from_trainer --- ## About static quants of https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-72B-v0.0 weighted/imatrix quants are available at https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-i1-GGUF ## 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](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.Q2_K.gguf) | Q2_K | 29.9 | | | [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.Q3_K_S.gguf) | Q3_K_S | 34.6 | | | [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.Q3_K_M.gguf) | Q3_K_M | 37.8 | lower quality | | [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.Q3_K_L.gguf) | Q3_K_L | 39.6 | | | [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.IQ4_XS.gguf) | IQ4_XS | 40.3 | | | [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.Q4_K_S.gguf) | Q4_K_S | 44.0 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.Q4_K_M.gguf) | Q4_K_M | 47.5 | fast, recommended | | [PART 1](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.Q5_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.Q5_K_S.gguf.part2of2) | Q5_K_S | 51.5 | | | [PART 1](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.Q5_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.Q5_K_M.gguf.part2of2) | Q5_K_M | 54.5 | | | [PART 1](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.Q6_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.Q6_K.gguf.part2of2) | Q6_K | 64.4 | very good quality | | [PART 1](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.Q8_0.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/EVA-Qwen2.5-72B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-72B-v0.0.Q8_0.gguf.part2of2) | Q8_0 | 77.4 | fast, best quality | Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.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](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/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.