Llama-3-8B-ProLong-SAO-Roleplay-512k

4
2
8.0B
llama
by
ZeroXClem
Language Model
OTHER
8B params
New
4 downloads
Early-stage
Try on Hugging FaceAdd to Compare
Edge AI:
Mobile
Laptop
Server
18GB+ RAM
Mobile
Laptop
Server
Quick Summary

AI model with specialized capabilities.

Device Compatibility

Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
8GB+ RAM

Training Data Analysis

🟡 Average (4.8/10)

Researched training datasets used by Llama-3-8B-ProLong-SAO-Roleplay-512k with quality assessment

Specialized For

general
science
multilingual
reasoning

Training Datasets (4)

common crawl
🔴 2.5/10
general
science
Key Strengths
  • •Scale and Accessibility: At 9.5+ petabytes, Common Crawl provides unprecedented scale for training d...
  • •Diversity: The dataset captures billions of web pages across multiple domains and content types, ena...
  • •Comprehensive Coverage: Despite limitations, Common Crawl attempts to represent the broader web acro...
Considerations
  • •Biased Coverage: The crawling process prioritizes frequently linked domains, making content from dig...
  • •Large-Scale Problematic Content: Contains significant amounts of hate speech, pornography, violent c...
c4
🔵 6/10
general
multilingual
Key Strengths
  • •Scale and Accessibility: 750GB of publicly available, filtered text
  • •Systematic Filtering: Documented heuristics enable reproducibility
  • •Language Diversity: Despite English-only, captures diverse writing styles
Considerations
  • •English-Only: Limits multilingual applications
  • •Filtering Limitations: Offensive content and low-quality text remain despite filtering
wikipedia
🟡 5/10
science
multilingual
Key Strengths
  • •High-Quality Content: Wikipedia articles are subject to community review, fact-checking, and citatio...
  • •Multilingual Coverage: Available in 300+ languages, enabling training of models that understand and ...
  • •Structured Knowledge: Articles follow consistent formatting with clear sections, allowing models to ...
Considerations
  • •Language Inequality: Low-resource language editions have significantly lower quality, fewer articles...
  • •Biased Coverage: Reflects biases in contributor demographics; topics related to Western culture and ...
arxiv
🟡 5.5/10
science
reasoning
Key Strengths
  • •Scientific Authority: Peer-reviewed content from established repository
  • •Domain-Specific: Specialized vocabulary and concepts
  • •Mathematical Content: Includes complex equations and notation
Considerations
  • •Specialized: Primarily technical and mathematical content
  • •English-Heavy: Predominantly English-language papers

Explore our comprehensive training dataset analysis

View All Datasets

Code Examples

YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments
YAML Configurationyaml
models:
  - model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
    # Base model: optimized for long-context interactions
  - model: Casual-Autopsy/L3-bluuwhale-SAO-MIX-8B-V1_fp32-merge-calc
    parameters:
      weight: 0.5  # Emphasizes roleplay elements without overshadowing the base
      density: 0.6  # Retains 60% of the significant parameters from the roleplay model

merge_method: della  # Ensures balanced integration of long-context and roleplay features
base_model: princeton-nlp/Llama-3-8B-ProLong-512k-Instruct
parameters:
  epsilon: 0.05  # Fine-tunes the granularity of pruning, maintaining key model features
  lambda: 1.0  # Harmonizes parameter influence from both models
  normalize: true  # Ensures stable alignment of merged parameters
  int8_mask: true  # Enhances memory efficiency for extended contexts

dtype: float32
out_dtype: bfloat16  # Balances precision and efficiency for versatile deployments

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