The editor of Downcodes learned that Hugging Face recently released a new AI tool called SmolLM, which is a series of small language models with parameter sizes ranging from 135M to 1.7B, aiming to provide efficient and powerful solutions for various devices and applications. AI capabilities. The SmolLM model can also run well on devices with limited resources, taking into account user privacy protection, and is very suitable for use on devices such as mobile phones and tablets.
Recently, Hugging Face launched a new AI tool-SmolLM. This is a series of high-performance small language models with parameters ranging from 135M to 1.7B, specially designed for a variety of devices and applications. It’s so cool to imagine these little models running efficiently on mobile phones and laptops!
The SmolLM model is characterized by its compactness and power. They can still perform well with less computing resources and help users protect privacy. Hugging Face used a data set called SmolLM-Corpus when training these models. This data set was carefully selected and contains rich educational and synthetic data to ensure that the model can learn a variety of knowledge.
Specifically, SmolLM has three versions: 135M, 360M and 1.7B parameters. These models can not only handle a variety of tasks, but can also run flexibly according to the user's hardware configuration. For example, the SmolLM-135M model has surpassed many similar products and has become the leader among models with less than 200M parameters.
The SmolLM model is evaluated on various benchmarks, testing commonsense reasoning and world knowledge. These models demonstrate impressive performance, outperforming other models in their respective size categories. For example, despite being trained on fewer tokens, the SmolLM-135M model outperforms MobileLM-125M, the current best model with less than 200M parameters. Likewise, the SmolLM-360M and SmolLM-1.7B models outperformed all other models with parameters less than 500M and 2B, respectively.
In addition to its excellent performance, SmolLM has also been specially tuned to make it better at understanding instructions and answering questions. Hugging Face also provides a demonstration of WebGPU so that everyone can directly experience the capabilities of these models.
The release of SmolLM proves that even small models can achieve amazing performance with high-quality training data.
Product entrance: https://top.aibase.com/tool/smollm
Highlight:
1. **Efficient Performance**: The SmolLM model can perform well under low computing resources and protect user privacy.
2. **Enrich data**: Use high-quality SmolLM-Corpus data set to ensure that the model learns diverse knowledge.
3. ? **Multiple applications**: Suitable for mobile phones, notebooks and other devices, flexible operation to meet different needs.
SmolLM brings new possibilities to the AI field with its efficient performance, rich knowledge reserves and wide application. The editor of Downcodes believes that SmolLM will play an important role in future AI applications. Hurry up and experience it!