MNLP Sft Model by eymericboyer

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MNLP Sft Model is an open-source language model by eymericboyer. Features: 596m LLM, VRAM: 2.4GB, Context: 32K, LLM Explorer Score: 0.19.

  Arxiv:1910.09700   Autotrain compatible   Conversational   Endpoints compatible   Qwen3   Region:us   Safetensors

MNLP Sft Model Benchmarks

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

MNLP Sft Model Parameters and Internals

LLM NameMNLP Sft Model
Repository 🤗https://huggingface.co/eymericboyer/MNLP_sft_model 
Model Size596m
Required VRAM2.4 GB
Updated2025-09-19
Maintainereymericboyer
Model Typeqwen3
Model Files  2.4 GB
Model ArchitectureQwen3ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.51.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typefloat32
Errorsreplace

Best Alternatives to MNLP Sft Model

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... Calling Qwen0.6B 27jul Merged40K / 1.2 GB6700
...Qwen0.6B 27jul Merged Llamacpp40K / 1.2 GB60
Sam Reason A140K / 2.4 GB201
Qwen3 0p6mimo S3 Bf16120032K / 1.2 GB1170
Qwen3 Grpo2 9632K / 1.2 GB50
Qwen3 0p6 Bf16 60032K / 1.2 GB60
MNLP M3 DPO Sft200k CME32K / 2.4 GB200
Rubi No Reason Phase 232K / 1.2 GB60
... Reason Phase Only Ultrafeed 132K / 1.2 GB90
Rubi No Reason Phase 132K / 1.2 GB70
Note: green Score (e.g. "73.2") means that the model is better than eymericboyer/MNLP_sft_model.

Rank the MNLP Sft Model 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