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TalktoaiZERO by shafire

 »  All LLMs  »  shafire  »  TalktoaiZERO   URL Share it on

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  Autotrain   Autotrain compatible Base model:meta-llama/llama-3.... Base model:quantized:meta-llam...   Conversational   Endpoints compatible   Gguf   Instruct   Llama   Lora   Peft   Q6   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/shafire/talktoaiZERO 

TalktoaiZERO Benchmarks

LLME Score: 0.24181
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
TalktoaiZERO (shafire/talktoaiZERO)

TalktoaiZERO Parameters and Internals

Model Type 
text-generation, multimodal
Use Cases 
Primary Use Cases:
Ethical-math decision-making, Advanced conversational AI, Quantum-math-inspired logic in AI responses, Intelligent Skynet style AI
Additional Notes 
Tested using Oogabooga web text generation with specific hardware requirements. Optimized for CPU usage.
Training Details 
Data Sources:
AutoTrain
Methodology:
Custom conversational training focused on ethical, quantum-based responses.
Input Output 
Output Format:
text
LLM NameTalktoaiZERO
Repository 🤗https://huggingface.co/shafire/talktoaiZERO 
Base Model(s)  meta-llama/Meta-Llama-3.1-8B-Instruct   meta-llama/Meta-Llama-3.1-8B-Instruct
Model Size8b
Required VRAM16.1 GB
Updated2024-12-22
Maintainershafire
Instruction-BasedYes
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   1.2 GB: 4-of-4   16.1 GB   6.6 GB
GGUF QuantizationYes
Quantization Typegguf|q6
Model ArchitectureAutoModelForCausalLM
Licensemit
Model Max Length2048
Is Biasednone
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|eot_id|>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesdown_proj|up_proj|gate_proj|q_proj|v_proj|k_proj|o_proj
LoRA Alpha32
LoRA Dropout0.05
R Param16

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Note: green Score (e.g. "73.2") means that the model is better than shafire/talktoaiZERO.

Rank the TalktoaiZERO Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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 v20241217
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