Text Classification
Transformers
TensorBoard
Safetensors
qwen2
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use JayHyeon/Qwen2-0.5B-Reward_1e-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JayHyeon/Qwen2-0.5B-Reward_1e-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JayHyeon/Qwen2-0.5B-Reward_1e-3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JayHyeon/Qwen2-0.5B-Reward_1e-3") model = AutoModelForSequenceClassification.from_pretrained("JayHyeon/Qwen2-0.5B-Reward_1e-3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a29a10eb51dba880581668152ececbf947c03360019a36a6de21bb576bdd7e6
- Size of remote file:
- 11.4 MB
- SHA256:
- bcfe42da0a4497e8b2b172c1f9f4ec423a46dc12907f4349c55025f670422ba9
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