Text Classification
Transformers
Safetensors
qwen2
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use mamba413/Qwen2-0.5B-Reward-DR-HH-Seed0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mamba413/Qwen2-0.5B-Reward-DR-HH-Seed0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mamba413/Qwen2-0.5B-Reward-DR-HH-Seed0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mamba413/Qwen2-0.5B-Reward-DR-HH-Seed0") model = AutoModelForSequenceClassification.from_pretrained("mamba413/Qwen2-0.5B-Reward-DR-HH-Seed0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 0, | |
| "eval_accuracy": 0.4, | |
| "eval_loss": 0.6474097967147827, | |
| "eval_runtime": 0.497, | |
| "eval_samples_per_second": 10.06, | |
| "eval_steps_per_second": 6.036 | |
| } |