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
metadata
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']