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

Autotrain compatible Base model:huggingfacetb/smoll... Base model:quantized:huggingfa... Conversational En Endpoints compatible Ext 8k 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: 1048 vs 1272 (so35)^-17.6%

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

MATH Lvl 5: 4.15

LLME Score: 0.51559

^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)

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

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	2025-01-29
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

Quantized Models of the SmolLM2 1.7B Instruct

Model	Likes	Downloads	VRAM
SmolLM2 1.7B Instruct Bnb 4bit	0	9326	1 GB

Best Alternatives to SmolLM2 1.7B Instruct

Best Alternatives	Context / RAM	Downloads	Likes
SmolTulu 1.7B Reinforced	8K / 3.4 GB	271	5
SmolLM2 1.7B Instruct	8K / 3.4 GB	6199	3
SmolLM2 1.7 Persona	8K / 3.5 GB	6	0
...RM 1 Smollm2 1.7B Lcot PyTorch	8K / 3.4 GB	141	0
SmolLM2 Math IIO 1.7B Instruct	8K / 3.4 GB	160	8
SmolLM2 1.7B Instruct	8K / 3.4 GB	142	3
Immy V3	8K / 3.4 GB	144	0
SmolLM 1.7B Instruct	2K / 3.4 GB	42594	107
SmolLM 1.7B Instruct	2K / 3.4 GB	5479	0
SmolLM 1.7B	2K / 3.4 GB	4603	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

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

Release v20241227

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