MegaBeam Mistral 7B 300K by amazon

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MegaBeam Mistral 7B 300K Benchmarks

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

Model Type 
language model
Use Cases 
Primary Use Cases:
processing long contexts
Limitations:
Ensure compliance with local regulations and quality standards.
Additional Notes 
Ensure model use complies with local regulations and quality standards.
Training Details 
Methodology:
fine-tuned
Context Length:
320000
Input Output 
Input Format:
320K max position embeddings.
Accepted Modalities:
text
LLM NameMegaBeam Mistral 7B 300K
Repository ๐Ÿค—https://huggingface.co/amazon/MegaBeam-Mistral-7B-300k 
Model Size7b
Required VRAM14.4 GB
Updated2025-03-19
Maintaineramazon
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 Length288800
Model Max Length288800
Transformers Version4.36.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16
MegaBeam Mistral 7B 300K (amazon/MegaBeam-Mistral-7B-300k)

Quantized Models of the MegaBeam Mistral 7B 300K

Model
Likes
Downloads
VRAM
MegaBeam Mistral 7B 300K Gguf3115 GB

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

Rank the MegaBeam Mistral 7B 300K 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124