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Swallow 7B Instruct GPTQ by TheBloke

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  4-bit   Autotrain compatible Base model:quantized:tokyotech... Base model:tokyotech-llm/swall...   En   Gptq   Instruct   Ja   Llama   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/Swallow-7B-Instruct-GPTQ 

Swallow 7B Instruct GPTQ Benchmarks

LLME Score: 0.16104
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Swallow 7B Instruct GPTQ (TheBloke/Swallow-7B-Instruct-GPTQ)

Swallow 7B Instruct GPTQ Parameters and Internals

Model Type 
llama, text-generation
Use Cases 
Areas:
research, commercial applications
Limitations:
The models are still in early stages and might not align well with human intent or safety considerations.
Additional Notes 
Trained primarily with additional Japanese language data to increase efficiency and representation.
Supported Languages 
Japanese (High), English (High)
Training Details 
Data Sources:
Japanese Wikipedia, RefinedWeb, Swallow Corpus, The Pile
Methodology:
Continual pre-training with supervised fine-tuning (SFT)
Context Length:
4096
Model Architecture:
llama2
Input Output 
Accepted Modalities:
text
Output Format:
text
LLM NameSwallow 7B Instruct GPTQ
Repository 🤗https://huggingface.co/TheBloke/Swallow-7B-Instruct-GPTQ 
Model NameSwallow 7B Instruct
Model Creatortokyotech-llm
Base Model(s)  Swallow 7B Instruct Hf   tokyotech-llm/Swallow-7b-instruct-hf
Model Size7b
Required VRAM4.1 GB
Updated2024-12-22
MaintainerTheBloke
Model Typellama
Instruction-BasedYes
Model Files  4.1 GB
Supported Languagesen ja
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size43176
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Swallow-7B-Instruct-GPTQ.

Rank the Swallow 7B Instruct GPTQ 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 v20241217
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