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MegaBeam Mistral 7B 300K Gguf by xceptor

 »  All LLMs  »  xceptor  »  MegaBeam Mistral 7B 300K Gguf   URL Share it on

  35   
  Autotrain compatible   Conversational   Gguf   Mistral   Q5   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/xceptor/MegaBeam-Mistral-7B-300k-gguf 

MegaBeam Mistral 7B 300K Gguf Benchmarks

LLME Score: 0.15504
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MegaBeam Mistral 7B 300K Gguf (xceptor/MegaBeam-Mistral-7B-300k-gguf)
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MegaBeam Mistral 7B 300K Gguf Parameters and Internals

Model Type 
fine-tuned, language model
Additional Notes 
The model can be deployed using vLLM, Sagemaker DJL, etc.
Training Details 
Context Length:
320000
Model Architecture:
Derived from Mistral-7B-Instruct-v0.2
Input Output 
Input Format:
Supports input contexts up to 320k tokens
LLM NameMegaBeam Mistral 7B 300K Gguf
Repository 🤗https://huggingface.co/xceptor/MegaBeam-Mistral-7B-300k-gguf 
Base Model(s)  MegaBeam Mistral 7B 300K   amazon/MegaBeam-Mistral-7B-300k
Model Size7b
Required VRAM5 GB
Updated2025-08-02
Maintainerxceptor
Model Typemistral
Model Files  5.1 GB   5.0 GB
GGUF QuantizationYes
Quantization Typegguf|q5|q5_k
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length288800
Model Max Length288800
Transformers Version4.36.0
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than xceptor/MegaBeam-Mistral-7B-300k-gguf.

Rank the MegaBeam Mistral 7B 300K Gguf Capabilities

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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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