--- base_model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1 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: other license_name: eva-llama3.3 quantized_by: mradermacher tags: - mergekit - merge --- ## About weighted/imatrix quants of https://huggingface.co/EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1 static quants are available at https://huggingface.co/mradermacher/EVA-LLaMA-3.33-70B-v0.1-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-LLaMA-3.33-70B-v0.1-i1-GGUF/resolve/main/EVA-LLaMA-3.33-70B-v0.1.i1-Q2_K.gguf) | i1-Q2_K | 26.5 | IQ3_XXS probably better | | [GGUF](https://huggingface.co/mradermacher/EVA-LLaMA-3.33-70B-v0.1-i1-GGUF/resolve/main/EVA-LLaMA-3.33-70B-v0.1.i1-IQ3_M.gguf) | i1-IQ3_M | 32.0 | | 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.