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Cognitivecomputations Dolphin 2.9 Llama3 8B 4bits by RichardErkhov

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  4-bit   Autotrain compatible   Axolotl   Bitsandbytes   Conversational   Endpoints compatible   Generated from trainer   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/RichardErkhov/cognitivecomputations_-_dolphin-2.9-llama3-8b-4bits 

Cognitivecomputations Dolphin 2.9 Llama3 8B 4bits Benchmarks

LLME Score: 0.187
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Cognitivecomputations Dolphin 2.9 Llama3 8B 4bits (RichardErkhov/cognitivecomputations_-_dolphin-2.9-llama3-8b-4bits)

Cognitivecomputations Dolphin 2.9 Llama3 8B 4bits Parameters and Internals

Model Type 
text generation, conversational AI
Use Cases 
Areas:
Research, Commercial Applications
Applications:
Conversational agents, Instruction-following tasks
Primary Use Cases:
Chatbots, Function calling support
Limitations:
May comply with unethical requests, Requires alignment for safe public deployment
Considerations:
Ensure ethical and responsible use by adding alignment layers.
Additional Notes 
Model is highly compliant with requests and lacks inherent ethical alignment which must be configured by users.
Training Details 
Data Sources:
cognitivecomputations/Dolphin-2.9, teknium/OpenHermes-2.5, m-a-p/CodeFeedback-Filtered-Instruction, cognitivecomputations/dolphin-coder, cognitivecomputations/samantha-data, HuggingFaceH4/ultrachat_200k, microsoft/orca-math-word-problems-200k, abacusai/SystemChat-1.1, Locutusque/function-calling-chatml, internlm/Agent-FLAN
Methodology:
Full Fine Tuning (FFT).
Context Length:
8000
Training Time:
2.5 days
Hardware Used:
8x L40S provided by Crusoe Cloud
Model Architecture:
AutoModelForCausalLM
Responsible Ai Considerations 
Fairness:
Filtered to remove alignment and bias.
Transparency:
Model architecture and dataset sources provided.
Accountability:
Users are responsible for content generated using this model.
Mitigation Strategies:
Recommend implementing user-specific alignment layer before deployment.
Input Output 
Input Format:
ChatML prompt template
Accepted Modalities:
text
Output Format:
Generated text responses
Performance Tips:
Add specific instructions in system messages to guide response behavior.
LLM NameCognitivecomputations Dolphin 2.9 Llama3 8B 4bits
Repository 🤗https://huggingface.co/RichardErkhov/cognitivecomputations_-_dolphin-2.9-llama3-8b-4bits 
Model Size8b
Required VRAM6.1 GB
Updated2025-02-22
MaintainerRichardErkhov
Model Typellama
Model Files  5.0 GB: 1-of-2   1.1 GB: 2-of-2
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.40.2
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|end_of_text|>
Vocabulary Size128258
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than RichardErkhov/cognitivecomputations_-_dolphin-2.9-llama3-8b-4bits.

Rank the Cognitivecomputations Dolphin 2.9 Llama3 8B 4bits Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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