Instructions to use suayptalha/MoE-Router with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suayptalha/MoE-Router with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="suayptalha/MoE-Router")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("suayptalha/MoE-Router") model = AutoModelForSequenceClassification.from_pretrained("suayptalha/MoE-Router", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| language: | |
| - en | |
| base_model: | |
| - distilbert/distilbert-base-uncased | |
| pipeline_tag: text-classification | |
| datasets: | |
| - FreedomIntelligence/medical-o1-reasoning-SFT | |
| - patrickfleith/instruction-freak-reasoning | |
| - ArdentTJ/t1_daily_conversations | |
| - nvidia/OpenCodeReasoning | |
| - nvidia/OpenMathReasoning | |
| library_name: transformers | |
| labels = ['code', 'if', 'math', 'medical'] |