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Pixel by NicklasMatzulla

 »  All LLMs  »  NicklasMatzulla  »  Pixel   URL Share it on

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Base model:mistralai/mistral-7... Base model:quantized:mistralai...   Conversational   En   Endpoints compatible   Gguf   Instruct   Mistral   Quantized   Region:us   Unsloth
Model Card on HF 🤗: https://huggingface.co/NicklasMatzulla/Pixel 

Pixel Benchmarks

LLME Score: 0.16225
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Pixel (NicklasMatzulla/Pixel)
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Pixel Parameters and Internals

Model Type 
text-generation-inference, transformers
Additional Notes 
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
LLM NamePixel
Repository 🤗https://huggingface.co/NicklasMatzulla/Pixel 
Base Model(s)  mistralai/Mistral-7B-Instruct-v0.3   mistralai/Mistral-7B-Instruct-v0.3
Model Size7b
Required VRAM4.4 GB
Updated2025-02-01
MaintainerNicklasMatzulla
Model Typemistral
Instruction-BasedYes
Model Files  14.5 GB   4.4 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModel
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.41.2
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|eot_id|>
Vocabulary Size128256
Torch Data Typebfloat16

Best Alternatives to Pixel

Best Alternatives
Context / RAM
Downloads
Likes
Mistral 7B Instruct V0.3 GGUF0K / 1.6 GB121474117
Qwen2 7B Instruct GGUF0K / 1.9 GB9221811
Mistral 7B Instruct V0.1 GGUF0K / 3.1 GB179733603
Mistral 7B Instruct V0.2 GGUF0K / 3.1 GB55713465
...hemeng Qwen Math 7b 24 1 100 10K / 15.2 GB390
Qwen2 7B Instruct V0.6 GGUF0K / 4.5 GB135220
Qwen2 7B Instruct V0.1 GGUF0K / 4.5 GB97140
Qwen2 7B Instruct V0.7 GGUF0K / 4.5 GB95300
Qwen2 7B Instruct V0.3 GGUF0K / 4.5 GB89111
Mistral 7B Instruct V0.3 GGUF0K / 2.7 GB1298810
Note: green Score (e.g. "73.2") means that the model is better than NicklasMatzulla/Pixel.

Rank the Pixel 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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