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SmolLM 1.7B Instruct by unsloth

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SmolLM 1.7B Instruct is an open-source language model by unsloth. Features: 1.7b LLM, VRAM: 3.4GB, Context: 2K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.16.

  Alignment-handbook Base model:finetune:huggingfac... Base model:huggingfacetb/smoll...   Conversational Dataset:bigcode/self-oss-instr... Dataset:huggingfacetb/everyday... Dataset:magpie-align/magpie-pr...   Dataset:teknium/openhermes-2.5   Deploy:azure   En   Endpoints compatible   Instruct   Llama   Region:us   Safetensors   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/unsloth/SmolLM-1.7B-Instruct 

SmolLM 1.7B Instruct Benchmarks

LLME Score: 0.15641
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
SmolLM 1.7B Instruct (unsloth/SmolLM-1.7B-Instruct)
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SmolLM 1.7B Instruct Parameters and Internals

LLM NameSmolLM 1.7B Instruct
Repository 🤗https://huggingface.co/unsloth/SmolLM-1.7B-Instruct 
Base Model(s)  HuggingFaceTB/SmolLM-1.7B-Instruct   HuggingFaceTB/SmolLM-1.7B-Instruct
Model Size1.7b
Required VRAM3.4 GB
Updated2026-05-13
Maintainerunsloth
Model Typellama
Instruction-BasedYes
Model Files  3.4 GB
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.44.2
Tokenizer ClassGPT2Tokenizer
Padding Token<empty_output>
Vocabulary Size49152
Torch Data Typebfloat16

Best Alternatives to SmolLM 1.7B Instruct

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SmolLM2 1.7B Instruct 16K16K / 3.4 GB15710
SmolLM2 1.7B Instruct8K / 3.4 GB182834728
SmolLM2 1.7B Instruct8K / 3.4 GB17476
...ygnis Alpha 1.7B V0.1 Instruct8K / 3.4 GB1702
SmolTulu 1.7B Reinforced8K / 3.4 GB115
SmolLM2 1.7 Persona8K / 3.5 GB970
Penny 1.7B8K / 6.9 GB17024
Superthoughts Lite V18K / 3.4 GB53
...ghts Lite 1.8B Experimental O18K / 3.6 GB162
Cllm 1.0.0 340000 Instruct8K / 3.5 GB50
Note: green Score (e.g. "73.2") means that the model is better than unsloth/SmolLM-1.7B-Instruct.

Rank the SmolLM 1.7B Instruct 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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