Text Classification
Transformers
Safetensors
qwen3
reward-model
prm
code-security
text-embeddings-inference
Instructions to use AetherPrior/qwen3-8b-impl-prm-exec-think with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AetherPrior/qwen3-8b-impl-prm-exec-think with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AetherPrior/qwen3-8b-impl-prm-exec-think")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AetherPrior/qwen3-8b-impl-prm-exec-think") model = AutoModelForSequenceClassification.from_pretrained("AetherPrior/qwen3-8b-impl-prm-exec-think", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4854819d2b6c0d452a5522153025461e1ca05e5924bd8d2ed20ca8523e4720f
- Size of remote file:
- 5 GB
- SHA256:
- 22bac32880175dfea2a415a5198d34711f624540dc52ca1147bb261911717a35
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