Text Classification
Transformers
Safetensors
qwen2
text-generation
llama-factory
lora
news-classification
chinese
deepseek-r1
qwen
text-embeddings-inference
Instructions to use real-jiakai/DeepSeek-R1-Distill-Qwen-7B-News-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use real-jiakai/DeepSeek-R1-Distill-Qwen-7B-News-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="real-jiakai/DeepSeek-R1-Distill-Qwen-7B-News-Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("real-jiakai/DeepSeek-R1-Distill-Qwen-7B-News-Classifier") model = AutoModelForMultimodalLM.from_pretrained("real-jiakai/DeepSeek-R1-Distill-Qwen-7B-News-Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7aacad7007a56f87b16368708645e2ac1f2a0addb7d85f23267dee4674a3d8ff
- Size of remote file:
- 4.88 GB
- SHA256:
- f1c0e20ed77ab161d4188f6a7a216f9514d5d09a0cc8591c3e03761c4923d3a8
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