Mistral 7B Instruct V0.2 Expanded Sec 1.6B Tokens by arcee-ai

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  Arxiv:2401.02415   Autotrain compatible   Conversational   Dataset:arcee-ai/sec-data-full   Endpoints compatible   Instruct   Mergekit   Mistral   Region:us   Safetensors   Sharded   Tensorflow

Mistral 7B Instruct V0.2 Expanded Sec 1.6B Tokens Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral 7B Instruct V0.2 Expanded Sec 1.6B Tokens (arcee-ai/Mistral-7B-Instruct-v0.2-expanded-sec-1.6B-tokens)

Mistral 7B Instruct V0.2 Expanded Sec 1.6B Tokens Parameters and Internals

Use Cases 
Primary Use Cases:
Can use with SEC data
Additional Notes 
Trained for a single epoch.
Training Details 
Data Volume:
1.6B SEC data
Methodology:
Only trained the newly added blocks as in the Llama pro paper while keeping every other layer frozen.
Hardware Used:
p5.48xlarge GPU (8 x 80GB)
Model Architecture:
Llama-pro style
LLM NameMistral 7B Instruct V0.2 Expanded Sec 1.6B Tokens
Repository ๐Ÿค—https://huggingface.co/arcee-ai/Mistral-7B-Instruct-v0.2-expanded-sec-1.6B-tokens 
Model Size7b
Required VRAM17.9 GB
Updated2025-02-22
Maintainerarcee-ai
Model Typemistral
Instruction-BasedYes
Model Files  4.9 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   3.1 GB: 4-of-4
Model ArchitectureMistralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.39.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat32

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Rank the Mistral 7B Instruct V0.2 Expanded Sec 1.6B Tokens Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227