L3-Rhaenys-8B

Name: L3-Rhaenys-8B
Rating: 8.8 (10 reviews)
Author: tannedbum

8.0B

1 language

llama

tannedbum

Language Model

OTHER

8B params

New

0 downloads

Early-stage

Try on Hugging Face Add to Compare

Edge AI:

Mobile

Laptop

Server

18GB+ RAM

Mobile

Laptop

Server

Quick Summary

3.0 Farewell model. Next i'm going to wait Sao10K to break the bank again with a new 3.1 RP base. This is a merge of pre-trained language models created using...

Device Compatibility

Mobile

4-6GB RAM

Laptop

16GB RAM

Server

GPU

Minimum Recommended

8GB+ RAM

Code Examples

SillyTaverntext

temp 0.9
top_k 30
top_p 0.75
min_p 0.2
rep_pen 1.1
smooth_factor 0.25
smooth_curve 1

SillyTaverntext

temp 0.9
top_k 30
top_p 0.75
min_p 0.2
rep_pen 1.1
smooth_factor 0.25
smooth_curve 1

SillyTaverntext

temp 0.9
top_k 30
top_p 0.75
min_p 0.2
rep_pen 1.1
smooth_factor 0.25
smooth_curve 1

SillyTaverntext

temp 0.9
top_k 30
top_p 0.75
min_p 0.2
rep_pen 1.1
smooth_factor 0.25
smooth_curve 1

SillyTaverntext

temp 0.9
top_k 30
top_p 0.75
min_p 0.2
rep_pen 1.1
smooth_factor 0.25
smooth_curve 1

SillyTaverntext

temp 0.9
top_k 30
top_p 0.75
min_p 0.2
rep_pen 1.1
smooth_factor 0.25
smooth_curve 1

SillyTaverntext

temp 0.9
top_k 30
top_p 0.75
min_p 0.2
rep_pen 1.1
smooth_factor 0.25
smooth_curve 1

Configurationyaml

slices:
  - sources:
      - model: Sao10K/L3-8B-Niitama-v1
        layer_range: [0, 32]
      - model: Sao10K/L3-8B-Stheno-v3.2
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Niitama-v1
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.6, 0.2, 0.4]
    - filter: mlp
      value: [0.8, 0.6, 0.4, 0.8, 0.6]
    - value: 0.4
dtype: bfloat16


slices:
  - sources:
      - model: tannedbum/L3-Niitama-Stheno-8B
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO-v0.2
        layer_range: [0, 32]
merge_method: slerp
base_model: tannedbum/L3-Niitama-Stheno-8B
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.6, 0.2, 0.4]
    - filter: mlp
      value: [0.8, 0.6, 0.4, 0.8, 0.6]
    - value: 0.4
dtype: bfloat16

Configurationyaml

slices:
  - sources:
      - model: Sao10K/L3-8B-Niitama-v1
        layer_range: [0, 32]
      - model: Sao10K/L3-8B-Stheno-v3.2
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Niitama-v1
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.6, 0.2, 0.4]
    - filter: mlp
      value: [0.8, 0.6, 0.4, 0.8, 0.6]
    - value: 0.4
dtype: bfloat16


slices:
  - sources:
      - model: tannedbum/L3-Niitama-Stheno-8B
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO-v0.2
        layer_range: [0, 32]
merge_method: slerp
base_model: tannedbum/L3-Niitama-Stheno-8B
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.6, 0.2, 0.4]
    - filter: mlp
      value: [0.8, 0.6, 0.4, 0.8, 0.6]
    - value: 0.4
dtype: bfloat16

Configurationyaml

slices:
  - sources:
      - model: Sao10K/L3-8B-Niitama-v1
        layer_range: [0, 32]
      - model: Sao10K/L3-8B-Stheno-v3.2
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Niitama-v1
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.6, 0.2, 0.4]
    - filter: mlp
      value: [0.8, 0.6, 0.4, 0.8, 0.6]
    - value: 0.4
dtype: bfloat16


slices:
  - sources:
      - model: tannedbum/L3-Niitama-Stheno-8B
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO-v0.2
        layer_range: [0, 32]
merge_method: slerp
base_model: tannedbum/L3-Niitama-Stheno-8B
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.6, 0.2, 0.4]
    - filter: mlp
      value: [0.8, 0.6, 0.4, 0.8, 0.6]
    - value: 0.4
dtype: bfloat16

Configurationyaml

slices:
  - sources:
      - model: Sao10K/L3-8B-Niitama-v1
        layer_range: [0, 32]
      - model: Sao10K/L3-8B-Stheno-v3.2
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Niitama-v1
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.6, 0.2, 0.4]
    - filter: mlp
      value: [0.8, 0.6, 0.4, 0.8, 0.6]
    - value: 0.4
dtype: bfloat16


slices:
  - sources:
      - model: tannedbum/L3-Niitama-Stheno-8B
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO-v0.2
        layer_range: [0, 32]
merge_method: slerp
base_model: tannedbum/L3-Niitama-Stheno-8B
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.6, 0.2, 0.4]
    - filter: mlp
      value: [0.8, 0.6, 0.4, 0.8, 0.6]
    - value: 0.4
dtype: bfloat16

Configurationyaml

slices:
  - sources:
      - model: Sao10K/L3-8B-Niitama-v1
        layer_range: [0, 32]
      - model: Sao10K/L3-8B-Stheno-v3.2
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Niitama-v1
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.6, 0.2, 0.4]
    - filter: mlp
      value: [0.8, 0.6, 0.4, 0.8, 0.6]
    - value: 0.4
dtype: bfloat16


slices:
  - sources:
      - model: tannedbum/L3-Niitama-Stheno-8B
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO-v0.2
        layer_range: [0, 32]
merge_method: slerp
base_model: tannedbum/L3-Niitama-Stheno-8B
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.6, 0.2, 0.4]
    - filter: mlp
      value: [0.8, 0.6, 0.4, 0.8, 0.6]
    - value: 0.4
dtype: bfloat16

Configurationyaml

slices:
  - sources:
      - model: Sao10K/L3-8B-Niitama-v1
        layer_range: [0, 32]
      - model: Sao10K/L3-8B-Stheno-v3.2
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Niitama-v1
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.6, 0.2, 0.4]
    - filter: mlp
      value: [0.8, 0.6, 0.4, 0.8, 0.6]
    - value: 0.4
dtype: bfloat16


slices:
  - sources:
      - model: tannedbum/L3-Niitama-Stheno-8B
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO-v0.2
        layer_range: [0, 32]
merge_method: slerp
base_model: tannedbum/L3-Niitama-Stheno-8B
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.6, 0.2, 0.4]
    - filter: mlp
      value: [0.8, 0.6, 0.4, 0.8, 0.6]
    - value: 0.4
dtype: bfloat16

Configurationyaml

slices:
  - sources:
      - model: Sao10K/L3-8B-Niitama-v1
        layer_range: [0, 32]
      - model: Sao10K/L3-8B-Stheno-v3.2
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Niitama-v1
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.6, 0.2, 0.4]
    - filter: mlp
      value: [0.8, 0.6, 0.4, 0.8, 0.6]
    - value: 0.4
dtype: bfloat16


slices:
  - sources:
      - model: tannedbum/L3-Niitama-Stheno-8B
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO-v0.2
        layer_range: [0, 32]
merge_method: slerp
base_model: tannedbum/L3-Niitama-Stheno-8B
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.6, 0.2, 0.4]
    - filter: mlp
      value: [0.8, 0.6, 0.4, 0.8, 0.6]
    - value: 0.4
dtype: bfloat16

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