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Model: mradermacher/EVA-Qwen2.5-14B-v0.2-i1-GGUF
Source: Original Platform

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README.md

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+---
+base_model: EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2
+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
+- cognitivecomputations/dolphin-2.9.3
+language:
+- en
+library_name: transformers
+license: apache-2.0
+quantized_by: mradermacher
+tags:
+- generated_from_trainer
+---
+## About
+
+<!-- ### quantize_version: 2 -->
+<!-- ### output_tensor_quantised: 1 -->
+<!-- ### convert_type: hf -->
+<!-- ### vocab_type:  -->
+<!-- ### tags: nicoboss -->
+weighted/imatrix quants of https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2
+
+<!-- provided-files -->
+static quants are available at https://huggingface.co/mradermacher/EVA-Qwen2.5-14B-v0.2-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://www.modelscope.cn/models/mradermacher/EVA-Qwen2.5-14B-v0.2-i1-GGUF/resolve/master/EVA-Qwen2.5-14B-v0.2.i1-IQ2_XS.gguf) | i1-IQ2_XS | 4.8 |  |
+| [GGUF](https://www.modelscope.cn/models/mradermacher/EVA-Qwen2.5-14B-v0.2-i1-GGUF/resolve/master/EVA-Qwen2.5-14B-v0.2.i1-IQ3_XS.gguf) | i1-IQ3_XS | 6.5 |  |
+| [GGUF](https://www.modelscope.cn/models/mradermacher/EVA-Qwen2.5-14B-v0.2-i1-GGUF/resolve/master/EVA-Qwen2.5-14B-v0.2.i1-IQ4_XS.gguf) | i1-IQ4_XS | 8.2 |  |
+| [GGUF](https://www.modelscope.cn/models/mradermacher/EVA-Qwen2.5-14B-v0.2-i1-GGUF/resolve/master/EVA-Qwen2.5-14B-v0.2.i1-Q4_K_M.gguf) | i1-Q4_K_M | 9.1 | fast, recommended |
+| [GGUF](https://www.modelscope.cn/models/mradermacher/EVA-Qwen2.5-14B-v0.2-i1-GGUF/resolve/master/EVA-Qwen2.5-14B-v0.2.i1-Q5_K_M.gguf) | i1-Q5_K_M | 10.6 |  |
+| [GGUF](https://www.modelscope.cn/models/mradermacher/EVA-Qwen2.5-14B-v0.2-i1-GGUF/resolve/master/EVA-Qwen2.5-14B-v0.2.i1-Q6_K.gguf) | i1-Q6_K | 12.2 | practically like static Q6_K |
+
+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.
+
+<!-- end -->
+