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Mistral Small 24B Instruct 2501 S1 SFT by yentinglin

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Mistral Small 24B Instruct 2501 S1 SFT is an open-source language model by yentinglin. Features: 24b LLM, VRAM: 47.3GB, Context: 32K, Instruction-Based, LLM Explorer Score: 0.18.

  Autotrain compatible Base model:finetune:mistralai/... Base model:mistralai/mistral-s...   Conversational Dataset:yentinglin/s1k-1.1-trl...   Endpoints compatible   Generated from trainer   Instruct   Mistral   Open-r1   Region:us   Safetensors   Sft   Sharded   Tensorflow   Trl
Model Card on HF 🤗: https://huggingface.co/yentinglin/Mistral-Small-24B-Instruct-2501-S1-SFT 

Mistral Small 24B Instruct 2501 S1 SFT Benchmarks

LLME Score: 0.17529
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral Small 24B Instruct 2501 S1 SFT (yentinglin/Mistral-Small-24B-Instruct-2501-S1-SFT)
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Mistral Small 24B Instruct 2501 S1 SFT Parameters and Internals

LLM NameMistral Small 24B Instruct 2501 S1 SFT
Repository 🤗https://huggingface.co/yentinglin/Mistral-Small-24B-Instruct-2501-S1-SFT 
Model NameMistral-Small-24B-Instruct-2501-S1-SFT
Base Model(s)  ...istral Small 24B Instruct 2501   mistralai/Mistral-Small-24B-Instruct-2501
Model Size24b
Required VRAM47.3 GB
Updated2025-02-15
Maintaineryentinglin
Model Typemistral
Instruction-BasedYes
Model Files  4.8 GB: 1-of-10   4.8 GB: 2-of-10   4.8 GB: 3-of-10   4.9 GB: 4-of-10   4.8 GB: 5-of-10   4.8 GB: 6-of-10   4.9 GB: 7-of-10   4.8 GB: 8-of-10   4.8 GB: 9-of-10   3.9 GB: 10-of-10   0.0 GB
Model ArchitectureMistralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.49.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size131072
Torch Data Typebfloat16

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MS3.2 PaintedFantasy V2 24B128K / 47.3 GB11940
Skyfall 31B V4128K / 62.9 GB634
Note: green Score (e.g. "73.2") means that the model is better than yentinglin/Mistral-Small-24B-Instruct-2501-S1-SFT.

Rank the Mistral Small 24B Instruct 2501 S1 SFT 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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