AI ExplorerAI Explorer
OutilsCatégoriesSitesLLMsComparerQuiz IAAlternativesPremium

—

Outils IA

—

Sites & Blogs

—

LLMs & Modèles

—

Catégories

AI Explorer

Trouvez et comparez les meilleurs outils d'intelligence artificielle pour vos projets.

Fait avecen France

Explorer

  • Tous les outils
  • Sites & Blogs
  • LLMs & Modèles
  • Comparer
  • Chatbots
  • Images IA
  • Code & Dev

Entreprise

  • Premium
  • À propos
  • Contact
  • Blog

Légal

  • Mentions légales
  • Confidentialité
  • CGV

© 2026 AI Explorer. Tous droits réservés.

AccueilLLMsQwen3 1.7B Base

Qwen3 1.7B Base

par Qwen

Open source · 323k downloads · 70 likes

2.3
(70 avis)ChatAPI & Local
À propos

Le modèle Qwen3 1.7B Base est une version allégée de la famille Qwen3, conçue pour offrir des capacités avancées de traitement du langage naturel. Entraîné sur un corpus multilingue de 36 000 milliards de tokens, il couvre 119 langues et excelle dans des domaines variés comme la programmation, les sciences, le raisonnement logique et la compréhension de textes longs. Grâce à une architecture optimisée et à un entraînement en trois phases, il combine stabilité, performance et une meilleure gestion des contextes étendus jusqu’à 32 000 tokens. Idéal pour des applications nécessitant une compréhension fine du langage, il se distingue par son équilibre entre efficacité et polyvalence, tout en restant accessible pour des déploiements légers.

Documentation

Qwen3-1.7B-Base

Qwen3 Highlights

Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Building upon extensive advancements in training data, model architecture, and optimization techniques, Qwen3 delivers the following key improvements over the previously released Qwen2.5:

  • Expanded Higher-Quality Pre-training Corpus: Qwen3 is pre-trained on 36 trillion tokens across 119 languages — tripling the language coverage of Qwen2.5 — with a much richer mix of high-quality data, including coding, STEM, reasoning, book, multilingual, and synthetic data.
  • Training Techniques and Model Architecture: Qwen3 incorporates a series of training techiques and architectural refinements, including global-batch load balancing loss for MoE models and qk layernorm for all models, leading to improved stability and overall performance.
  • Three-stage Pre-training: Stage 1 focuses on broad language modeling and general knowledge acquisition, Stage 2 improves reasoning skills like STEM, coding, and logical reasoning, and Stage 3 enhances long-context comprehension by extending training sequence lengths up to 32k tokens.
  • Scaling Law Guided Hyperparameter Tuning: Through comprehensive scaling law studies across the three-stage pre-training pipeline, Qwen3 systematically tunes critical hyperparameters — such as learning rate scheduler and batch size — separately for dense and MoE models, resulting in better training dynamics and final performance across different model scales.

Model Overview

Qwen3-1.7B-Base has the following features:

  • Type: Causal Language Models
  • Training Stage: Pretraining
  • Number of Parameters: 1.7B
  • Number of Paramaters (Non-Embedding): 1.4B
  • Number of Layers: 28
  • Number of Attention Heads (GQA): 16 for Q and 8 for KV
  • Context Length: 32,768

For more details, including benchmark evaluation, hardware requirements, and inference performance, please refer to our blog, GitHub, and Documentation.

Requirements

The code of Qwen3 has been in the latest Hugging Face transformers and we advise you to use the latest version of transformers.

With transformers<4.51.0, you will encounter the following error:

VB.NET
KeyError: 'qwen3'

Evaluation & Performance

Detailed evaluation results are reported in this 📑 blog.

Citation

If you find our work helpful, feel free to give us a cite.

INI
@misc{qwen3technicalreport,
      title={Qwen3 Technical Report}, 
      author={Qwen Team},
      year={2025},
      eprint={2505.09388},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2505.09388}, 
}
Liens & Ressources
Spécifications
CatégorieChat
AccèsAPI & Local
LicenceOpen Source
TarificationOpen Source
Paramètres7B parameters
Note
2.3

Essayer Qwen3 1.7B Base

Accédez directement au modèle