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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ language:
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+ - en
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+ tags:
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+ - 32 bit upscale
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+ - full 32 bit precision
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+ - master files
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+ ---
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+ <h3> Master Files for Ultra High Quality Remasters of "Psyonic-Cetacean" 20B </h3>
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+
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+ <img src="science-mad.jpg" width=300px height=300px style="float:right; padding:5px;">
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+
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+ May "Space Whale" swim in the oceans of the universe forever!
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+
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+ This repo contains the full precision (32 bit) master files for 32 bit upscales created by "DavidAU" of:
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+
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+ https://huggingface.co/DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF-imatrix
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+
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+ And
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+
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+ https://huggingface.co/DavidAU/Psyonic-Cetacean-Ultra-Quality-20b-GGUF
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+
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+ Please view either repo for details on the remaster's results, and other important infomation.
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+
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+ <font color="red"><B>IMPORTANT NOTES For Maximum Results: </b></font>
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+
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+ These are "final" result files of the full precision rebuild (including end result merge(s)) minus
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+ GGUF and Imatrix level upscaling / adjustments which occuring during "GGUFing" processes.
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+
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+ If you use these to create your own GGUFs, please use "outfile" at F32 for best results. If
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+ you use F16 this will reduce the quality by a factor of 2 or higher.
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+
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+ Imatrix processes should use a stable dataset(s) of at least 500 "chunks" or more.
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+ If smaller dataset(s) are used this may corrupt or reduce the quality of the Imatrix builds.
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+
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+ Due to the precision remaster there will be "greater" distance between each quant - both
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+ non imatrix and imatrix.
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+
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+ IE: The jump in quality, instruction following, "ai brainpower", nuance and output
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+ between Q4 and Q5 and likewise Q5 and Q6 will be larger than normal.
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+
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+ Same applies to "Imatrix" quants.
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+
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+ In addition there will also be differences between exact Imatrix and non-imatrix quants
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+ especially in terms of "creative uses" and/or uses where there is no "right answer".
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+
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+ Finally, in terms of prompts:
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+
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+ You may find longer prompts are no longer required and/or you may need to reduce the size
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+ of prompts in usage. This is a factor due to the precision upscale.
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+
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+ Doing this will ensure the quality of the upscale is maximized in the GGUFs.
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+
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+ /* GPTQers:
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+
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+ Suggest 4bit-Act32 TRUE for best results.
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+
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+ /* EXL2ers:
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+
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+ Suggest Min 4.5 BPW or higher ; 6 BPW and up is especially potent.
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+ Strongly suggest you do not reduce layer bit count, as this will affect depth and nuance.
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+ The more BPW the better.
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+
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+ Happy GGUFing, EXL2ing, GPTQing, AWQing, HQQing and of course "Merging".
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+
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+ <b>LONG LIVE OPEN SOURCE!</B>
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+
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+ <I>DavidAU</I>
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+
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+ /* Drop me a note when up, and I will link the masters to your repos.
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config.json ADDED
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+ {
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+ "_name_or_path": "F:/13B/Orca-2-13b_flat",
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 5120,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 13824,
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+ "max_position_embeddings": 4096,
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+ "mlp_bias": false,
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+ "model_type": "llama",
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+ "num_attention_heads": 40,
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+ "num_hidden_layers": 62,
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+ "num_key_value_heads": 40,
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+ "pad_token_id": 0,
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+ "pretraining_tp": 1,
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": null,
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+ "rope_theta": 10000.0,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.42.0.dev0",
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+ "use_cache": true,
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+ "vocab_size": 32000,
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+ "quantization_config": {
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+ "quant_method": "exl2",
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+ "version": "0.1.3",
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+ "bits": 4.0,
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+ "head_bits": 6,
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+ "calibration": {
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+ "rows": 100,
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+ "length": 2048,
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+ "dataset": "(default)"
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+ }
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+ }
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+ }
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