Triangle104
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Update README.md
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README.md
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---
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license: llama3
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license_name: llama3
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license_link: LICENSE
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library_name: transformers
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@@ -22,6 +22,73 @@ base_model: crestf411/L3.1-8B-Slush-v1.1
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This model was converted to GGUF format from [`crestf411/L3.1-8B-Slush-v1.1`](https://huggingface.co/crestf411/L3.1-8B-Slush-v1.1) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/crestf411/L3.1-8B-Slush-v1.1) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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@@ -60,4 +127,4 @@ Step 3: Run inference through the main binary.
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or
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```
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./llama-server --hf-repo Triangle104/L3.1-8B-Slush-v1.1-Q4_K_S-GGUF --hf-file l3.1-8b-slush-v1.1-q4_k_s.gguf -c 2048
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```
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license: llama3.1
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license_name: llama3
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license_link: LICENSE
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library_name: transformers
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This model was converted to GGUF format from [`crestf411/L3.1-8B-Slush-v1.1`](https://huggingface.co/crestf411/L3.1-8B-Slush-v1.1) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/crestf411/L3.1-8B-Slush-v1.1) for more details on the model.
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---
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Model details:
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Slush is a two-stage model trained with high LoRA dropout, where stage 1 is a pretraining continuation on the base model, aimed at boosting the model's creativity and writing capabilities. This is then merged into the instruction tune model, and stage 2 is a fine tuning step on top of this to further enhance its roleplaying capabilities and/or to repair any damage caused in the stage 1 merge.
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This is an initial experiment done on the at-this-point-infamous Llama 3.1 8B model, in an attempt to retain its smartness while addressing its abysmal lack of imagination/creativity. As always, feedback is welcome, and begone if you demand perfection.
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The second stage, like the Sunfall series, follows the Silly Tavern preset, so ymmv in particular if you use some other tool and/or preset.
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This update (v1.1) addresses some of the feedback from the first iteration by ramping down the training parameters, and also introduces a custom merge using mergekit.
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Parameter suggestions:
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I did all my testing with temp 1, min-p 0.1, DRY 0.8. I enabled XTC at higher contexts.
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Training details:
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Stage 1 (continued pretraining)
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Target: meta-llama/Llama-3.1-8B (resulting LoRA merged into meta-llama/Llama-3.1-8B-Instruct)
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LoRA dropout 0.5 (motivation)
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LoRA rank 64, alpha 128 (motivation)
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LR cosine 4e-6
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LoRA+ with LR Ratio: 15
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Context size: 16384
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Gradient accumulation steps: 4
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Epochs: 1
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Stage 2 (fine tune)
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Target: Stage 1 model
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LoRA dropout 0.5
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LoRA rank 32, alpha 64
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LR cosine 5e-6 (min 5e-7)
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LoRA+ with LR Ratio: 15
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Context size: 16384
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Gradient accumulation steps: 4
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Epochs: 2
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Merge Method
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This model was merged using the TIES merge method using meta-llama/Llama-3.1-8B as a base.
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Configuration
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The following YAML configuration was used to produce this model:
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models:
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- model: stage1-on-instruct
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parameters:
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weight: 1.5
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density: 1
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- model: stage2-on-stage1
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parameters:
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weight: 1.5
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density: 1
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- model: meta-llama/Llama-3.1-8B-Instruct
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parameters:
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weight: 1
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density: 1
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merge_method: ties
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base_model: meta-llama/Llama-3.1-8B
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parameters:
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weight: 1
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density: 1
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normalize: true
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int8_mask: true
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tokenizer_source: meta-llama/Llama-3.1-8B-Instruct
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dtype: bfloat16
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---
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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or
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```
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./llama-server --hf-repo Triangle104/L3.1-8B-Slush-v1.1-Q4_K_S-GGUF --hf-file l3.1-8b-slush-v1.1-q4_k_s.gguf -c 2048
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```
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