Text Classification
Transformers
TensorBoard
Safetensors
qwen3
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use selink/Qwen3-4B-fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selink/Qwen3-4B-fa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="selink/Qwen3-4B-fa")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("selink/Qwen3-4B-fa") model = AutoModelForSequenceClassification.from_pretrained("selink/Qwen3-4B-fa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8be1c312d4707ccfabe3f8d2fd73a286effeb4d80f644e8e6c8c75c63b4348a6
- Size of remote file:
- 5.62 kB
- SHA256:
- 76e5c201f45c8e75068a5a3c92d60364b3ed91975d8d5a09c8dc89eaa94c9c80
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