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MegaBeam Mistral 7B 300K by amazon

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  Autotrain compatible   Conversational   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/amazon/MegaBeam-Mistral-7B-300k 

MegaBeam Mistral 7B 300K Benchmarks

MMLU Pro: 17.21
GPQA: 3.13
MUSR: 8.35
BBH: 19.29
IFEval: 52.03 vs 88 (so35)-40.9%
MATH Lvl 5: 2.11
LLME Score: 0.27212
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 (amazon/MegaBeam-Mistral-7B-300k)

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 🤗https://huggingface.co/amazon/MegaBeam-Mistral-7B-300k 
Model Size7b
Required VRAM14.4 GB
Updated2025-03-04
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

Quantized Models of the MegaBeam Mistral 7B 300K

Model
Likes
Downloads
VRAM
MegaBeam Mistral 7B 300K Gguf3725 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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Release v20241227
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