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Tia 70B RP by Dogge

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  4-bit   4bit   Autotrain compatible Base model:quantized:unsloth/l... Base model:unsloth/llama-3-70b...   Bitsandbytes   Conversational   En   Endpoints compatible   Instruct   Llama   Quantized   Region:us   Safetensors   Sft   Sharded   Tensorflow   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/Dogge/Tia-70B-RP 

Tia 70B RP Benchmarks

LLME Score: 0.14949
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Tia 70B RP (Dogge/Tia-70B-RP)
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Tia 70B RP Parameters and Internals

Model Type 
text-generation-inference, transformers, unsloth, llama, trl, sft
Additional Notes 
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
LLM NameTia 70B RP
Repository 🤗https://huggingface.co/Dogge/Tia-70B-RP 
Base Model(s)  Llama 3 70B Instruct Bnb 4bit   unsloth/llama-3-70b-Instruct-bnb-4bit
Model Size70b
Required VRAM141.9 GB
Updated2025-09-23
MaintainerDogge
Model Typellama
Instruction-BasedYes
Model Files  4.6 GB: 1-of-30   4.7 GB: 2-of-30   5.0 GB: 3-of-30   5.0 GB: 4-of-30   4.7 GB: 5-of-30   4.7 GB: 6-of-30   4.7 GB: 7-of-30   5.0 GB: 8-of-30   5.0 GB: 9-of-30   4.7 GB: 10-of-30   4.7 GB: 11-of-30   4.7 GB: 12-of-30   5.0 GB: 13-of-30   5.0 GB: 14-of-30   4.7 GB: 15-of-30   4.7 GB: 16-of-30   4.7 GB: 17-of-30   5.0 GB: 18-of-30   5.0 GB: 19-of-30   4.7 GB: 20-of-30   4.7 GB: 21-of-30   4.7 GB: 22-of-30   5.0 GB: 23-of-30   5.0 GB: 24-of-30   4.7 GB: 25-of-30   4.7 GB: 26-of-30   4.7 GB: 27-of-30   5.0 GB: 28-of-30   5.0 GB: 29-of-30   2.1 GB: 30-of-30
Supported Languagesen
Quantization Type4bit
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.40.0
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|end_of_text|>
Vocabulary Size128256
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than Dogge/Tia-70B-RP.

Rank the Tia 70B RP 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 v20241124
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