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RichardErkhov/
Elfrino_-_PsyMedRose-20B-gguf

Name: Elfrino_-_PsyMedRose-20B-gguf
Availability: InStock

endpoints_compatible

gguf

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Quantization made by Richard Erkhov.

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PsyMedRose-20B - GGUF

Model creator: https://huggingface.co/Elfrino/
Original model: https://huggingface.co/Elfrino/PsyMedRose-20B/

Name	Quant method	Size
PsyMedRose-20B.Q2_K.gguf	Q2_K	6.91GB
PsyMedRose-20B.IQ3_XS.gguf	IQ3_XS	7.63GB
PsyMedRose-20B.IQ3_S.gguf	IQ3_S	8.06GB
PsyMedRose-20B.Q3_K_S.gguf	Q3_K_S	8.06GB
PsyMedRose-20B.IQ3_M.gguf	IQ3_M	8.53GB
PsyMedRose-20B.Q3_K.gguf	Q3_K	9.04GB
PsyMedRose-20B.Q3_K_M.gguf	Q3_K_M	9.04GB
PsyMedRose-20B.Q3_K_L.gguf	Q3_K_L	9.9GB
PsyMedRose-20B.IQ4_XS.gguf	IQ4_XS	10.01GB
PsyMedRose-20B.Q4_0.gguf	Q4_0	10.52GB
PsyMedRose-20B.IQ4_NL.gguf	IQ4_NL	10.57GB
PsyMedRose-20B.Q4_K_S.gguf	Q4_K_S	10.59GB
PsyMedRose-20B.Q4_K.gguf	Q4_K	11.22GB
PsyMedRose-20B.Q4_K_M.gguf	Q4_K_M	11.22GB
PsyMedRose-20B.Q4_1.gguf	Q4_1	11.67GB
PsyMedRose-20B.Q5_0.gguf	Q5_0	12.83GB
PsyMedRose-20B.Q5_K_S.gguf	Q5_K_S	12.83GB
PsyMedRose-20B.Q5_K.gguf	Q5_K	13.18GB
PsyMedRose-20B.Q5_K_M.gguf	Q5_K_M	13.18GB
PsyMedRose-20B.Q5_1.gguf	Q5_1	13.98GB
PsyMedRose-20B.Q6_K.gguf	Q6_K	15.28GB
PsyMedRose-20B.Q8_0.gguf	Q8_0	19.79GB

Original model description:

base_model:

Undi95/PsyMedRP-v1-20B
tavtav/Rose-20B library_name: transformers tags:
mergekit
merge

Creative and coherent, more tests needed...

A SLERP merge of two nice models:

Undi95/PsyMedRP-v1-20B

and

tavtav/Rose-20B

#############################################################

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

yaml

slices:
  - sources:
      - model: Undi95/PsyMedRP-v1-20B
        layer_range: [0, 62]  # PsyMedRP has 62 layers
      - model: tavtav/Rose-20B
        layer_range: [0, 62]  # Rose-20B has 62 layers
merge_method: slerp  # Or use another method like weight_average if needed
base_model: Undi95/PsyMedRP-v1-20B  # PsyMedRP as the base for reasoning dominance
parameters:
  t:
    - filter: self_attn
      value: [0.3, 0.7, 1, 0.7, 0.4]  # Boost creativity in pattern recognition
    - filter: mlp
      value: [0.2, 0.6, 1, 0.8, 0.5]  # Emphasize creativity in decision-making and connections
    - value: 0.639  # Slight leaning toward PsyMedRP's base characteristics
dtype: bfloat16

RichardErkhov/Elfrino_-_PsyMedRose-20B-gguf