L3-Nymeria-Maid-8B

2
12
8.0B
1 language
llama
by
tannedbum
Language Model
OTHER
8B params
New
2 downloads
Early-stage
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Edge AI:
Mobile
Laptop
Server
18GB+ RAM
Mobile
Laptop
Server
Quick Summary

This version is solely for scientific purposes, of course.

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-Stheno-v3.2
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Stheno-v3.2
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.4, 0.6]
    - filter: mlp
      value: [0.8, 0.6, 0.6, 0.4]
    - value: 0.4
dtype: bfloat16
Configurationyaml
slices:
  - sources:
      - model: Sao10K/L3-8B-Stheno-v3.2
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Stheno-v3.2
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.4, 0.6]
    - filter: mlp
      value: [0.8, 0.6, 0.6, 0.4]
    - value: 0.4
dtype: bfloat16
Configurationyaml
slices:
  - sources:
      - model: Sao10K/L3-8B-Stheno-v3.2
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Stheno-v3.2
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.4, 0.6]
    - filter: mlp
      value: [0.8, 0.6, 0.6, 0.4]
    - value: 0.4
dtype: bfloat16
Configurationyaml
slices:
  - sources:
      - model: Sao10K/L3-8B-Stheno-v3.2
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Stheno-v3.2
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.4, 0.6]
    - filter: mlp
      value: [0.8, 0.6, 0.6, 0.4]
    - value: 0.4
dtype: bfloat16
Configurationyaml
slices:
  - sources:
      - model: Sao10K/L3-8B-Stheno-v3.2
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Stheno-v3.2
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.4, 0.6]
    - filter: mlp
      value: [0.8, 0.6, 0.6, 0.4]
    - value: 0.4
dtype: bfloat16
Configurationyaml
slices:
  - sources:
      - model: Sao10K/L3-8B-Stheno-v3.2
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Stheno-v3.2
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.4, 0.6]
    - filter: mlp
      value: [0.8, 0.6, 0.6, 0.4]
    - value: 0.4
dtype: bfloat16
Configurationyaml
slices:
  - sources:
      - model: Sao10K/L3-8B-Stheno-v3.2
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Stheno-v3.2
parameters:
  t:
    - filter: self_attn
      value: [0.2, 0.4, 0.4, 0.6]
    - filter: mlp
      value: [0.8, 0.6, 0.6, 0.4]
    - value: 0.4
dtype: bfloat16

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