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Cat Llama 3 70B Instruct Bpw2.25 EXL2 by blockblockblock

 »  All LLMs  »  blockblockblock  »  Cat Llama 3 70B Instruct Bpw2.25 EXL2   URL Share it on

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  Autotrain compatible   Conversational   Endpoints compatible   Exl2   Instruct   Llama   Pytorch   Quantized   Region:us   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/blockblockblock/Cat-Llama-3-70B-instruct-bpw2.25-exl2 

Cat Llama 3 70B Instruct Bpw2.25 EXL2 Benchmarks

LLME Score: 0.18316
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Cat Llama 3 70B Instruct Bpw2.25 EXL2 (blockblockblock/Cat-Llama-3-70B-instruct-bpw2.25-exl2)

Cat Llama 3 70B Instruct Bpw2.25 EXL2 Parameters and Internals

Model Type 
Text Generation
Use Cases 
Areas:
General Science, Biosciences
Applications:
Role Play, Chatbot interactions
Primary Use Cases:
System Instruction fidelity, Character immersion
Additional Notes 
Model aims to provide system prompt fidelity, helpful interactions, and role play character immersion.
Training Details 
Data Sources:
Huggingface dataset, GPT-4 responses, Chat Doctor
Methodology:
Finetuned for system prompt fidelity, helpfulness, and character engagement.
Training Time:
14 days
Hardware Used:
16*A100 GPUs
Model Architecture:
Finetuned version of Llama 3
LLM NameCat Llama 3 70B Instruct Bpw2.25 EXL2
Repository 🤗https://huggingface.co/blockblockblock/Cat-Llama-3-70B-instruct-bpw2.25-exl2 
Model Size70b
Required VRAM22.2 GB
Updated2025-02-16
Maintainerblockblockblock
Model Typellama
Instruction-BasedYes
Model Files  8.5 GB: 1-of-3   8.6 GB: 2-of-3   5.1 GB: 3-of-3
Quantization Typeexl2
Model ArchitectureLlamaForCausalLM
Context Length8192
Model Max Length8192
Transformers Version4.40.1
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 blockblockblock/Cat-Llama-3-70B-instruct-bpw2.25-exl2.

Rank the Cat Llama 3 70B Instruct Bpw2.25 EXL2 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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