Quantization made by Richard Erkhov.
This repo contains the full bf16 weights of a merge of pre-trained language models created using
mergekit.
Unorthodox contributions to this merge include a biomedical model, a roleplay-focused model, a Japanese language model, and a Korean language model; the original base model was an abliterated model combined with a cybersecurity model. A merger of two recent preference optimization models was also included to shore up reasoning, with the expectation that overall good reasoning and coherence will contribute to narrative flow. Roleplay text generation appears to be easily steered toward emotionally intelligent characters. It should be noted that the vast majority of merge contributions (as measured by weight) were not intended for roleplay.
Tested with 8k context length, temperature=1, and minP=0.01 using Instruct prompts for Llama 3. Example Llama 3 presets can be
downloaded here. Specifically, "Llama 3 Lukewarm Presets 8k context.json" corresponds to test settings.
Example context templates variants tested with Llama 3 can be
downloaded here; their corresponding Instruct prompts can be
downloaded here. Specifically, the two "Llama 3 Instruct Safety.json" files correspond to test settings.
Care should be taken when using this model, as it is possible that harmful outputs may be generated. Given that this model is derivative, responsible use is further mandated by the
WhiteRabbitNeo Usage Restrictions Extension to the Llama-3 License. This model is further subject to CC-BY-NC-4.0 by default, meaning that commercial use is restricted, barring an alternative licensing agreement.
Built with Meta Llama 3.
This model was merged using the
task arithmetic merge method using
grimjim/llama-3-Nephilim-v1-8B as a base.
1base_model: grimjim/llama-3-Nephilim-v1-8B
2dtype: bfloat16
3merge_method: task_arithmetic
4parameters:
5 normalize: false
6slices:
7- sources:
8 - layer_range: [0, 32]
9 model: grimjim/llama-3-Nephilim-v1-8B
10 - layer_range: [0, 32]
11 model: grimjim/Llama-3-Instruct-8B-SPPO-Iter3-SimPO-merge
12 parameters:
13 weight: 0.62
14 - layer_range: [0, 32]
15 model: openlynn/Llama-3-Soliloquy-8B-v2
16 parameters:
17 weight: 0.03
18 - layer_range: [0, 32]
19 model: tokyotech-llm/Llama-3-Swallow-8B-Instruct-v0.1
20 parameters:
21 weight: 0.2
22 - layer_range: [0, 32]
23 model: MLP-KTLim/llama-3-Korean-Bllossom-8B
24 parameters:
25 weight: 0.001
26 - layer_range: [0, 32]
27 model: grimjim/llama-3-aaditya-OpenBioLLM-8B
28 parameters:
29 weight: 0.03
30
Detailed results can be found
here
