Mistral Pretraining by ericmelz

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Mistral Pretraining is an open-source language model by ericmelz. Features: 84.5m LLM, VRAM: 0.3GB, Context: 0.5K, LLM Explorer Score: 0.2.

  Autotrain compatible   Endpoints compatible   Generated from trainer   Mistral   Region:us   Safetensors

Mistral Pretraining Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Mistral Pretraining Parameters and Internals

LLM NameMistral Pretraining
Repository 🤗https://huggingface.co/ericmelz/mistral-pretraining 
Model Size84.5m
Required VRAM0.3 GB
Updated2025-11-22
Maintainerericmelz
Model Typemistral
Model Files  0.3 GB   0.0 GB
Model ArchitectureMistralForCausalLM
Context Length512
Model Max Length512
Transformers Version4.54.0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat32

Best Alternatives to Mistral Pretraining

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Context / RAM
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Mistral Pretrained Test128K / 0.3 GB70
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Lab 20.5K / 0.3 GB60
Mistral Pre Trained Model0.5K / 0.3 GB60
Mistral Pretraining0.5K / 0.3 GB50
Mistral Pretraining0.5K / 0.3 GB60
Mistral Pretraining0.5K / 0.3 GB60
Mistral Pretraining0.5K / 0.3 GB60
Mistral Pretraining0.5K / 0.3 GB50

Rank the Mistral Pretraining 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 v20260328a