Text Classification
Transformers
Safetensors
qwen3
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use LiberteEPFL/qwen3-1.7b-rm-full-bigchat-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LiberteEPFL/qwen3-1.7b-rm-full-bigchat-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LiberteEPFL/qwen3-1.7b-rm-full-bigchat-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LiberteEPFL/qwen3-1.7b-rm-full-bigchat-v2") model = AutoModelForSequenceClassification.from_pretrained("LiberteEPFL/qwen3-1.7b-rm-full-bigchat-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38e4fa842f1a1d849257f65cd9dbaa1ca96da1544c78377ddb850a25d42ffda3
- Size of remote file:
- 6.23 kB
- SHA256:
- 6a588166e9457d7c8118073b6bd5512b5b81f399e679b391d93a1324f2d2a304
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