Text Classification
Transformers
TensorBoard
Safetensors
qwen2
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use JayHyeon/Qwen2-0.5B-Reward_VPO_5e-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_VPO_5e-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_VPO_5e-3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JayHyeon/Qwen2-0.5B-Reward_VPO_5e-3") model = AutoModelForSequenceClassification.from_pretrained("JayHyeon/Qwen2-0.5B-Reward_VPO_5e-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 188 Bytes
4936c16 | 1 2 3 4 5 6 7 8 | {
"epoch": 1.0,
"eval_accuracy": 0.536,
"eval_loss": 0.6894727945327759,
"eval_runtime": 36.386,
"eval_samples_per_second": 27.483,
"eval_steps_per_second": 0.879
} |