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LLaVA NeXT Video 7B by lmms-lab

 »  All LLMs  »  lmms-lab  »  LLaVA NeXT Video 7B   URL Share it on

  1095   
  Autotrain compatible   Llava   Region:us   Safetensors   Sharded   Tensorflow   Video-text-to-text
Model Card on HF 🤗: https://huggingface.co/lmms-lab/LLaVA-NeXT-Video-7B 

LLaVA NeXT Video 7B Benchmarks

LLME Score: 0.19523
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
LLaVA NeXT Video 7B (lmms-lab/LLaVA-NeXT-Video-7B)

LLaVA NeXT Video 7B Parameters and Internals

Model Type 
multimodal, chatbot
Use Cases 
Areas:
Research
Primary Use Cases:
Research on large multimodal models and chatbots
Training Details 
Data Sources:
LAION/CC/SBU, BLIP, GPT-generated, VQA academic tasks, GPT-4V, ShareGPT
Methodology:
Fine-tuning LLM on multimodal instruction-following data
LLM NameLLaVA NeXT Video 7B
Repository 🤗https://huggingface.co/lmms-lab/LLaVA-NeXT-Video-7B 
Model Size7b
Required VRAM14.1 GB
Updated2025-04-19
Maintainerlmms-lab
Model Typellava
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.2 GB: 3-of-3   0.0 GB   0.0 GB
Model ArchitectureLlavaLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.39.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16

Best Alternatives to LLaVA NeXT Video 7B

Best Alternatives
Context / RAM
Downloads
Likes
Llava Merged Finetuned 7b32K / 15.1 GB141
Llava V1.6 Mistral 7B PATCHED32K / 15.1 GB18
KoLLaVA V1.5 Synatra 7B32K / 15.1 GB4138
Llava V1.5 7B4K / 13.5 GB1322575446
LLaVA NeXT Video 7B DPO4K / 14.2 GB1356527
Llava V1.6 Vicuna 7B4K / 14.1 GB29036122
Vip Llava 7B4K / 14.2 GB664868
Table Llava V1.5 7B4K / 14.2 GB25312
RLAIF V 7B4K / 14.1 GB39910
Vlm Rlaif Video Llava 7b4K / 14.2 GB110
Note: green Score (e.g. "73.2") means that the model is better than lmms-lab/LLaVA-NeXT-Video-7B.

Rank the LLaVA NeXT Video 7B 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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