SmolLM2 1.7B Instruct By HuggingFaceTB: Benchmarks, Features and Detailed Analysis. Insights on SmolLM2 1.7B Instruct.

Arxiv:2502.02737 Autotrain compatible Base model:huggingfacetb/smoll... Base model:quantized:huggingfa... Conversational En Endpoints compatible Instruct Llama Onnx Region:us Safetensors Tensorboard Transformers.js

Model Card on HF 🤗: https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B-Instruct

SmolLM2 1.7B Instruct Benchmarks

LMSys ELO: 1055 vs 1272 (so35)^-17.1%

IFEval: 53.68 vs 88 (so35)^-39%

MATH Lvl 5: 5.82

LLME Score: 0.46174

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

What is the LLM Explorer Rank (Score)

🌟 Advertise your project 🚀

SmolLM2 1.7B Instruct Parameters and Internals

Model Type

text generation, instruction following

Use Cases

Areas:

text generation, instruction following, text rewriting, summarization, function calling

Applications:

educational tools, coding assistance, customer support, chatbots, language learning

Primary Use Cases:

text and instruction generation

Limitations:

primarily understands and generates content in English, generated content may not always be factually accurate or free from bias

Considerations:

Users should always verify important information and critically evaluate any generated content.

Supported Languages

en (main)

Training Details

Data Sources:

FineWeb-Edu, DCLM, The Stack, new mathematics and coding datasets

Data Volume:

11T tokens

Methodology:

Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO)

Hardware Used:

256 H100 GPUs

Model Architecture:

Transformer decoder

Input Output

Input Format:

Expected input format includes system and user prompts

Accepted Modalities:

text

Output Format:

text

Performance Tips:

Ensure queries are clear and check model's language support for optimal results.

LLM Name	SmolLM2 1.7B Instruct
Repository 🤗	https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B-Instruct
Base Model(s)	HuggingFaceTB/SmolLM2-1.7B HuggingFaceTB/SmolLM2-1.7B
Model Size	1.7b
Required VRAM	3.4 GB
Updated	2025-06-09
Maintainer	HuggingFaceTB
Model Type	llama
Instruction-Based	Yes
Model Files	3.4 GB 0.0 GB
Supported Languages	en
Context Length	8k
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.42.3
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|im_end\|>
Vocabulary Size	49152
Torch Data Type	bfloat16

SmolLM2 1.7B Instruct (HuggingFaceTB/SmolLM2-1.7B-Instruct)

Quantized Models of the SmolLM2 1.7B Instruct

Model	Likes	Downloads	VRAM
SmolLM2 1.7B Instruct Bnb 4bit	2	1048	1 GB

Best Alternatives to SmolLM2 1.7B Instruct

Best Alternatives	Context / RAM	Downloads	Likes
SmolLM2 1.7B Instruct 16K	16K / 3.4 GB	16	9
Penny 1.7B	8K / 6.9 GB	237	23
SmolTulu 1.7B Reinforced	8K / 3.4 GB	477	5
Superthoughts Lite V1	8K / 3.4 GB	20	3
SmolLM2 1.7 Persona	8K / 3.5 GB	18	0
SmolLM2 1.7B Instruct	8K / 3.4 GB	3192	4
...ghts Lite 1.8B Experimental O1	8K / 3.6 GB	22	2
Cllm 1.0.0 340000 Instruct	8K / 3.5 GB	13	0
SmolLM2 1.7B Open Thought	8K / 3.4 GB	27	0
SmolLM2 1.7B R1 Distilled	8K / 3.4 GB	12	0

Rank the SmolLM2 1.7B Instruct 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

What open-source LLMs or SLMs are you in search of? 48046 in total.

Email us: info@extractum.io. Our Privacy Policy | Terms and Conditions | Suggest an improvement.

Our Social Media →

Original data from HuggingFace, OpenCompass and various public git repos.

Release v20241124

Support LLM Explorer