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Small Mistral 1 by ThorBaller

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Small Mistral 1 is an open-source language model by ThorBaller. Features: 3.9b LLM, VRAM: 2.3GB, Context: 4K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.14.

  4-bit   4bit Base model:quantized:unsloth/p... Base model:unsloth/phi-3-mini-...   Bitsandbytes   Conversational   Dataset:qiaojin/pubmedqa   En   Endpoints compatible   Instruct   Mistral   Quantized   Region:us   Safetensors   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/ThorBaller/small_mistral_1 

Small Mistral 1 Benchmarks

LLME Score: 0.13553
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Small Mistral 1 (ThorBaller/small_mistral_1)
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Small Mistral 1 Parameters and Internals

Model Type 
text-generation-inference
Additional Notes 
The model was developed with Unsloth and the Huggingface TRL library.
Training Details 
Methodology:
Trained 2x faster with Unsloth and Huggingface's TRL library.
LLM NameSmall Mistral 1
Repository 🤗https://huggingface.co/ThorBaller/small_mistral_1 
Base Model(s)  ...hi 3 Mini 4K Instruct Bnb 4bit   unsloth/Phi-3-mini-4k-instruct-bnb-4bit
Model Size3.9b
Required VRAM2.3 GB
Updated2026-05-19
MaintainerThorBaller
Model Typemistral
Instruction-BasedYes
Model Files  2.3 GB
Supported Languagesen
Quantization Type4bit
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.41.2
Tokenizer ClassLlamaTokenizer
Padding Token<|placeholder6|>
Vocabulary Size32064
Torch Data Typefloat16

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...hi 3 Mini 4K Instruct Bnb 4bit4K / 2.3 GB3686943
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MediChat Medium4K / 2.3 GB51
...Spydaz Web AI ChatQA 002 4 BIT512K / 4.1 GB240
Spydaz Web AI 02 4 BIT32K / 4.1 GB280
...pydaz Web AI ChatQA BASE 4 BIT32K / 4.1 GB180
...3 Mini 4K Instruct Ita Orpo V24K / 2.3 GB60
Note: green Score (e.g. "73.2") means that the model is better than ThorBaller/small_mistral_1.

Rank the Small Mistral 1 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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