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Akam Product NER GPT J 6B 4bit Merged by janani4office2

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  4bit   Autotrain compatible   Endpoints compatible   Gptj   Pytorch   Quantized   Region:us   Sharded

Akam Product NER GPT J 6B 4bit Merged Benchmarks

LLME Score: 0.15296
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Akam Product NER GPT J 6B 4bit Merged Parameters and Internals

LLM NameAkam Product NER GPT J 6B 4bit Merged
Repository 🤗https://huggingface.co/janani4office2/akam_product_NER_GPT-J-6b-4bit-merged 
Model Size6b
Required VRAM2.5 GB
Updated2024-09-07
Maintainerjanani4office2
Model Typegptj
Model Files  0.9 GB: 1-of-5   0.9 GB: 2-of-5   0.7 GB: 3-of-5   0.0 GB: 4-of-5   0.0 GB: 5-of-5
Quantization Type4bit
Model ArchitectureGPTJForCausalLM
Model Max Length2048
Transformers Version4.34.0.dev0
Tokenizer ClassGPT2Tokenizer
Beginning of Sentence Token<|endoftext|>
End of Sentence Token<|endoftext|>
Unk Token<|endoftext|>
Vocabulary Size50400
Torch Data Typefloat32
Activation Functiongelu_new
Errorsreplace
Akam Product NER GPT J 6B 4bit Merged (janani4office2/akam_product_NER_GPT-J-6b-4bit-merged)

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Note: green Score (e.g. "73.2") means that the model is better than janani4office2/akam_product_NER_GPT-J-6b-4bit-merged.

Rank the Akam Product NER GPT J 6B 4bit Merged Capabilities

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Release v2024072803
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