Feature Extraction
Transformers
Safetensors
multilingual
qwen3_5_text
qwen3.5
classification-backbone
text-classification
knowledge-distillation
model-compression
edge-ai
Instructions to use mp-juuuns/qwen35-standalone4l-classification-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mp-juuuns/qwen35-standalone4l-classification-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="mp-juuuns/qwen35-standalone4l-classification-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("mp-juuuns/qwen35-standalone4l-classification-base") model = AutoModel.from_pretrained("mp-juuuns/qwen35-standalone4l-classification-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d84aa8f7459ddadc0d15b89eadab5208455fc7d4ab695161bc1780a9ca8f24ea
- Size of remote file:
- 668 MB
- SHA256:
- 2732c616772fe320cdea228ab4554981418b1b2bf615c4183fb1ac8e6e2168d3
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