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Llama 3.1 70B FLDx2 Tess3 Abliterated Fusion Norm by Nexesenex

 »  All LLMs  »  Nexesenex  »  Llama 3.1 70B FLDx2 Tess3 Abliterated Fusion Norm   URL Share it on

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  Merged Model   Autotrain compatible Base model:hitachi-nlp/llama-3... Base model:migtissera/tess-3-l...   Conversational   Endpoints compatible   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Nexesenex/Llama_3.1_70b_FLDx2-Tess3_abliterated_fusion_norm 

Llama 3.1 70b FLDx2 Tess3 Abliterated Fusion Norm Benchmarks

LLME Score: 0.26524
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 3.1 70B FLDx2 Tess3 Abliterated Fusion Norm (Nexesenex/Llama_3.1_70b_FLDx2-Tess3_abliterated_fusion_norm)

Llama 3.1 70B FLDx2 Tess3 Abliterated Fusion Norm Parameters and Internals

LLM NameLlama 3.1 70b FLDx2 Tess3 Abliterated Fusion Norm
Repository 🤗https://huggingface.co/Nexesenex/Llama_3.1_70b_FLDx2-Tess3_abliterated_fusion_norm 
Base Model(s)  hitachi-nlp/Llama-3.1-70B-FLDx2   migtissera/Tess-3-Llama-3.1-70B   hitachi-nlp/Llama-3.1-70B-FLDx2   migtissera/Tess-3-Llama-3.1-70B
Merged ModelYes
Model Size70b
Required VRAM141.9 GB
Updated2025-04-30
MaintainerNexesenex
Model Typellama
Model Files  4.7 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   2.0 GB: 30-of-30
Model ArchitectureLlamaForCausalLM
Context Length131072
Model Max Length131072
Transformers Version4.51.1
Tokenizer ClassPreTrainedTokenizer
Padding Token<hono_pad>
Vocabulary Size128257
Torch Data Typebfloat16

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