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
| [build-system] | |
| requires = ["setuptools>=68"] | |
| build-backend = "setuptools.build_meta" | |
| [project] | |
| name = "qwen35-classification-distill" | |
| version = "0.1.0" | |
| description = "Auditable Qwen3.5 24L→8L→6L→4L classification distillation" | |
| requires-python = ">=3.11" | |
| dependencies = [ | |
| "torch>=2.4", | |
| "transformers==5.13.0", | |
| "safetensors>=0.4", | |
| "PyYAML>=6", | |
| "pyarrow>=16", | |
| ] | |
| [project.scripts] | |
| qwen35-distill = "qwen35_distill.cli:main" | |
| [tool.setuptools] | |
| packages = ["qwen35_distill"] | |