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Qwen2 7B Instruct Llama by Minami-su

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  Autotrain compatible   Chat   Conversational   En   Endpoints compatible   Instruct   Llama   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/Minami-su/Qwen2-7B-Instruct-llama 

Qwen2 7B Instruct Llama Benchmarks

LLME Score: 0.20498
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2 7B Instruct Llama (Minami-su/Qwen2-7B-Instruct-llama)

Qwen2 7B Instruct Llama Parameters and Internals

Model Type 
text generation
Supported Languages 
en (fluent)
Input Output 
Input Format:
chat template
Accepted Modalities:
text
Output Format:
text
LLM NameQwen2 7B Instruct Llama
Repository 🤗https://huggingface.co/Minami-su/Qwen2-7B-Instruct-llama 
Model Size7b
Required VRAM15.2 GB
Updated2024-12-21
MaintainerMinami-su
Model Typellama
Instruction-BasedYes
Model Files  2.0 GB: 1-of-8   1.9 GB: 2-of-8   1.9 GB: 3-of-8   2.0 GB: 4-of-8   1.9 GB: 5-of-8   1.9 GB: 6-of-8   2.0 GB: 7-of-8   1.6 GB: 8-of-8
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to Qwen2 7B Instruct Llama

Best Alternatives
Context / RAM
Downloads
Likes
... Qwen2.5llamaify 7B V23.1 200K195K / 15.2 GB29820
SuperNeuralDreadDevil 8B128K / 16.1 GB1871
Falcon3 7B Instruct32K / 14.8 GB367628
Falcon3 7B Instruct 1.58bit32K / 3.3 GB36213
FalconSlerp2 7B32K / 14.9 GB60
Llama 2 7B 32K Instruct32K / 13.5 GB6318159
Qwen2 7B Instruct Mistral32K / 15.2 GB131
AIRIC The Mistral32K / 14.4 GB7577
...ls Vikhr 7B Instruct 0.4 4bits32K / 5.2 GB80
Vikhr 7B Instruct 0.332K / 14.6 GB394
Note: green Score (e.g. "73.2") means that the model is better than Minami-su/Qwen2-7B-Instruct-llama.

Rank the Qwen2 7B Instruct Llama 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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