Text Classification
Transformers
Safetensors
English
Chinese
jp
qwen3
Generated from Trainer
reward-trainer
trl
text-embeddings-inference
Instructions to use puwaer/Safe-Reward-Qwen3-1.7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use puwaer/Safe-Reward-Qwen3-1.7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="puwaer/Safe-Reward-Qwen3-1.7B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("puwaer/Safe-Reward-Qwen3-1.7B") model = AutoModelForSequenceClassification.from_pretrained("puwaer/Safe-Reward-Qwen3-1.7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from puwaer/Safe-Reward-Qwen3-1.7B: direct link, hf CLI and curl.
- Browser
- Download file 6.1 kB
-
https://huggingface.co/puwaer/Safe-Reward-Qwen3-1.7B/resolve/main/training_args.bin
- Command line
-
hf download hf://puwaer/Safe-Reward-Qwen3-1.7B/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/puwaer/Safe-Reward-Qwen3-1.7B/resolve/main/training_args.bin
6.1 kB
- Xet hash:
- 9f3159a47ef3a1ffa6d19d120d3611bea2e07774fcc4120797ed21472131c44e
- Size of remote file:
- 6.1 kB
- SHA256:
- 0bac374be2d5ed5c13a9c48e6da3de3cc4eb964b53bfe27d88490e40efc34760
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