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TinyMistral 248M by Locutusque

 »  All LLMs  »  Locutusque  »  TinyMistral 248M   URL Share it on

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  Autotrain compatible   Dataset:jeankaddour/minipile   Dataset:skylion007/openwebtext   En   Endpoints compatible   Mistral   Pytorch   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/Locutusque/TinyMistral-248M 

TinyMistral 248M Benchmarks

LLME Score: 0.18121
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
TinyMistral 248M (Locutusque/TinyMistral-248M)

TinyMistral 248M Parameters and Internals

Model Type 
text-generation
Use Cases 
Primary Use Cases:
fine-tuning on a downstream task
Additional Notes 
This model aims to prove trillion-scale datasets are not necessary for language model pretraining.
Supported Languages 
en (fluent)
Training Details 
Data Sources:
Skylion007/openwebtext, JeanKaddour/minipile
Data Volume:
7,488,000 examples
Context Length:
32768
Hardware Used:
single GPU (Titan V)
Input Output 
Accepted Modalities:
text
Output Format:
text-generation
LLM NameTinyMistral 248M
Repository 🤗https://huggingface.co/Locutusque/TinyMistral-248M 
Model Size248m
Required VRAM1 GB
Updated2024-12-22
MaintainerLocutusque
Model Typemistral
Model Files  1.0 GB   1.0 GB
Supported Languagesen
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.35.0
Tokenizer ClassLlamaTokenizer
Padding Token[PAD]
Vocabulary Size32005
Torch Data Typefloat16

Best Alternatives to TinyMistral 248M

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Context / RAM
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TinyMistral 248M V2.532K / 1 GB58627
TinyMistral 248M V232K / 1 GB140517
TinyMistral 248M V2.5 Instruct32K / 1 GB2711
...al V2.5 MiniPile Guidelines E132K / 0.6 GB362
TinyMistral V2 Test132K / 1 GB181
TinyMistral 248M 8bits32K / 0.3 GB181
Tinymistv132K / 0.5 GB170
TinyMistral 248M Instruct32K / 1 GB2811
TinyMistral Haiku32K / 1 GB160
...istral 248M V2.5 Instruct Orpo32K / 0.5 GB190
Note: green Score (e.g. "73.2") means that the model is better than Locutusque/TinyMistral-248M.

Rank the TinyMistral 248M Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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 v20241217
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