CorticalStack_-_shadow-clown-7B-slerp-gguf

RichardErkhov/CorticalStack_-_shadow-clown-7B-slerp-gguf

CorticalStack_-_shadow-clown-7B-slerp-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.

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82.2 GB

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Hugging Face

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.gguf95.2 GB · 100%

At a glance

Access: Public
Created: Sep 13, 2024
Updated: Sep 13, 2024
SHA: bc202e2e

Model card

From the Hugging Face model README

Quantization made by Richard Erkhov.

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shadow-clown-7B-slerp - GGUF

Model creator: https://huggingface.co/CorticalStack/
Original model: https://huggingface.co/CorticalStack/shadow-clown-7B-slerp/

Name	Quant method	Size
shadow-clown-7B-slerp.Q2_K.gguf	Q2_K	2.53GB
shadow-clown-7B-slerp.IQ3_XS.gguf	IQ3_XS	2.81GB
shadow-clown-7B-slerp.IQ3_S.gguf	IQ3_S	2.96GB
shadow-clown-7B-slerp.Q3_K_S.gguf	Q3_K_S	2.95GB
shadow-clown-7B-slerp.IQ3_M.gguf	IQ3_M	3.06GB
shadow-clown-7B-slerp.Q3_K.gguf	Q3_K	3.28GB
shadow-clown-7B-slerp.Q3_K_M.gguf	Q3_K_M	3.28GB
shadow-clown-7B-slerp.Q3_K_L.gguf	Q3_K_L	3.56GB
shadow-clown-7B-slerp.IQ4_XS.gguf	IQ4_XS	3.67GB
shadow-clown-7B-slerp.Q4_0.gguf	Q4_0	3.83GB
shadow-clown-7B-slerp.IQ4_NL.gguf	IQ4_NL	3.87GB
shadow-clown-7B-slerp.Q4_K_S.gguf	Q4_K_S	3.86GB
shadow-clown-7B-slerp.Q4_K.gguf	Q4_K	4.07GB
shadow-clown-7B-slerp.Q4_K_M.gguf	Q4_K_M	4.07GB
shadow-clown-7B-slerp.Q4_1.gguf	Q4_1	4.24GB
shadow-clown-7B-slerp.Q5_0.gguf	Q5_0	4.65GB
shadow-clown-7B-slerp.Q5_K_S.gguf	Q5_K_S	4.65GB
shadow-clown-7B-slerp.Q5_K.gguf	Q5_K	4.78GB
shadow-clown-7B-slerp.Q5_K_M.gguf	Q5_K_M	4.78GB
shadow-clown-7B-slerp.Q5_1.gguf	Q5_1	5.07GB
shadow-clown-7B-slerp.Q6_K.gguf	Q6_K	5.53GB
shadow-clown-7B-slerp.Q8_0.gguf	Q8_0	7.17GB

Original model description:

license: apache-2.0 tags:

merge
mergekit
Gille/StrangeMerges_32-7B-slerp
yam-peleg/Experiment26-7B

shadow-clown-7B-slerp

shadow-clown-7B-slerp is a DARE merge of the following models using mergekit:

See the paper Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch for more on the method.

🧩 Configuration

slices:
  - sources:
      - model: CorticalStack/pastiche-crown-clown-7b-dare-dpo
        layer_range: [0, 32]
      - model: MSL7/INEX12-7b
        layer_range: [0, 32]
merge_method: slerp
base_model: CorticalStack/pastiche-crown-clown-7b-dare-dpo
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

slices:
  - sources:
      - model: liminerity/M7-7b
        layer_range: [0, 32]
      - model: CorticalStack/pastiche-crown-clown-7b-dare-dpo
        layer_range: [0, 32]
merge_method: slerp
base_model: liminerity/M7-7b
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16


slices:
  - sources:
      - model: ammarali32/multi_verse_model
        layer_range: [0, 32]
      - model: liminerity/merge
        layer_range: [0, 32]
merge_method: slerp
base_model: ammarali32/multi_verse_model
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16


slices:
  - sources:
      - model: Gille/StrangeMerges_32-7B-slerp
        layer_range: [0, 32]
      - model: yam-peleg/Experiment26-7B
        layer_range: [0, 32]
merge_method: slerp
base_model: Gille/StrangeMerges_32-7B-slerp
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

Created: Sep 13, 2024
Updated: Sep 13, 2024