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Swallow 70B NVE Instruct Hf by tokyotech-llm

 »  All LLMs  »  tokyotech-llm  »  Swallow 70B NVE Instruct Hf   URL Share it on

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  Arxiv:2404.17733   Arxiv:2404.17790   Autotrain compatible   En   Endpoints compatible   Instruct   Ja   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/tokyotech-llm/Swallow-70b-NVE-instruct-hf 

Swallow 70B NVE Instruct Hf Benchmarks

LLME Score: 0.15779
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Swallow 70B NVE Instruct Hf (tokyotech-llm/Swallow-70b-NVE-instruct-hf)

Swallow 70B NVE Instruct Hf Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Research, Commercial applications
Limitations:
Models not tuned to ensure outputs align with human intent and safety considerations.
Additional Notes 
The models are continually pre-trained and instruction-tuned, emphasizing Japanese language capabilities.
Supported Languages 
supported_languages_list (Japanese, English), languages_details (The Swallow model has undergone continual pre-training with the addition of Japanese language data.)
Training Details 
Data Sources:
Japanese Wikipedia, RefinedWeb, Swallow Corpus, The Pile
Methodology:
Supervised fine-tuning (SFT) and instruction tuning using Anthropic HH-RLHF, Databricks Dolly 15-k, and OpenAssistant Conversations Dataset.
Model Architecture:
Refer to LLaMA-2 technical report for details on the model architecture.
Input Output 
Accepted Modalities:
text
Output Format:
Text
Performance Tips:
Model employs a tokenizer with a broadened vocabulary based on Japanese data, offering efficient text representation and faster inference.
Release Notes 
Version:
0.1
Date:
April 26, 2024
Notes:
Release of Swallow-7b-instruct-v0.1, Swallow-13b-instruct-v0.1, and Swallow-70b-instruct-v0.1.
Version:
N/A
Date:
March 2, 2024
Notes:
Release of Swallow-7b-plus-hf with twice as many Japanese tokens as Swallow-7b-hf.
Version:
N/A
Date:
February 4, 2024
Notes:
Release of Swallow-13b-NVE-hf.
Version:
N/A
Date:
January 26, 2024
Notes:
Release of Swallow-7b-NVE-hf, Swallow-7b-NVE-instruct-hf, Swallow-70b-NVE-hf, Swallow-70b-NVE-instruct-hf.
Version:
N/A
Date:
December 19, 2023
Notes:
Release of Swallow-7b-hf, Swallow-7b-instruct-hf, Swallow-13b-hf, Swallow-13b-instruct-hf, Swallow-70b-hf, Swallow-70b-instruct-hf.
LLM NameSwallow 70B NVE Instruct Hf
Repository 🤗https://huggingface.co/tokyotech-llm/Swallow-70b-NVE-instruct-hf 
Model Size70b
Required VRAM138.7 GB
Updated2025-02-22
Maintainertokyotech-llm
Model Typellama
Instruction-BasedYes
Model Files  4.7 GB: 1-of-29   4.7 GB: 2-of-29   5.0 GB: 3-of-29   5.0 GB: 4-of-29   4.7 GB: 5-of-29   4.7 GB: 6-of-29   4.7 GB: 7-of-29   5.0 GB: 8-of-29   5.0 GB: 9-of-29   4.7 GB: 10-of-29   4.7 GB: 11-of-29   4.7 GB: 12-of-29   5.0 GB: 13-of-29   5.0 GB: 14-of-29   4.7 GB: 15-of-29   4.7 GB: 16-of-29   4.7 GB: 17-of-29   5.0 GB: 18-of-29   5.0 GB: 19-of-29   4.7 GB: 20-of-29   4.7 GB: 21-of-29   4.7 GB: 22-of-29   5.0 GB: 23-of-29   5.0 GB: 24-of-29   4.7 GB: 25-of-29   4.7 GB: 26-of-29   4.7 GB: 27-of-29   5.0 GB: 28-of-29   3.8 GB: 29-of-29
Supported Languagesen ja
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.33.2
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than tokyotech-llm/Swallow-70b-NVE-instruct-hf.

Rank the Swallow 70B NVE Instruct Hf 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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