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Mistral 7B Instruct V0.2 Function Calling by InterSync

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  Autotrain compatible   Conversational   Endpoints compatible   Function-call   Instruct   Mistral   Region:us   Safetensors   Sharded   Tensorflow

Mistral 7B Instruct V0.2 Function Calling Benchmarks

LLME Score: 0.19498
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 Function Calling Parameters and Internals

LLM NameMistral 7B Instruct V0.2 Function Calling
Repository 🤗https://huggingface.co/InterSync/Mistral-7B-Instruct-v0.2-Function-Calling 
Model Size7b
Required VRAM14.7 GB
Updated2024-10-18
MaintainerInterSync
Model Typemistral
Instruction-BasedYes
Model Files  0.9 GB: 1-of-15   1.0 GB: 2-of-15   1.0 GB: 3-of-15   1.0 GB: 4-of-15   1.0 GB: 5-of-15   1.0 GB: 6-of-15   1.0 GB: 7-of-15   1.0 GB: 8-of-15   1.0 GB: 9-of-15   1.0 GB: 10-of-15   1.0 GB: 11-of-15   1.0 GB: 12-of-15   1.0 GB: 13-of-15   1.0 GB: 14-of-15   0.8 GB: 15-of-15
Model ArchitectureMistralForCausalLM
Licensecc
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16
Mistral 7B Instruct V0.2 Function Calling (InterSync/Mistral-7B-Instruct-v0.2-Function-Calling)

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Note: green Score (e.g. "73.2") means that the model is better than InterSync/Mistral-7B-Instruct-v0.2-Function-Calling.

Rank the Mistral 7B Instruct V0.2 Function Calling Capabilities

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803
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