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Agent 7B V1 128K by Vezora

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Agent 7B V1 128K is an open-source language model by Vezora. Features: 7b LLM, VRAM: 14.4GB, Context: 128K, License: apache-2.0, LLM Explorer Score: 0.12.

  Dataset:m-a-p/code-feedback   Endpoints compatible   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Vezora/Agent-7b-v1-128k 

Agent 7B V1 128K Benchmarks

LLME Score: 0.11852
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Agent 7B V1 128K (Vezora/Agent-7b-v1-128k)
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Agent 7B V1 128K Parameters and Internals

Use Cases 
Areas:
interactive code performance
Applications:
TaskWeaver, OpenInterpreter
Training Details 
Data Sources:
m-a-p/Code-Feedback
Data Volume:
31,000 examples over 3 epochs
Methodology:
Trained back to the standard Mistral EOS token `~~`, used Unsloth qlora library.
Context Length:
128000
Training Time:
37 hours
Hardware Used:
single Nvidia 3090
LLM NameAgent 7B V1 128K
Repository 🤗https://huggingface.co/Vezora/Agent-7b-v1-128k 
Model Size7b
Required VRAM14.4 GB
Updated2026-05-13
MaintainerVezora
Model Typemistral
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.39.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32002
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than Vezora/Agent-7b-v1-128k.

Rank the Agent 7B V1 128K 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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