Text Classification
Transformers
Safetensors
qwen2
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use mamba413/Qwen2-0.5B-Reward-DR-SIMU 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-SIMU 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-SIMU")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mamba413/Qwen2-0.5B-Reward-DR-SIMU") model = AutoModelForSequenceClassification.from_pretrained("mamba413/Qwen2-0.5B-Reward-DR-SIMU", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mamba413/Qwen2-0.5B-Reward-DR-SIMU: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/mamba413/Qwen2-0.5B-Reward-DR-SIMU/resolve/main/training_args.bin
- Command line
-
hf download hf://mamba413/Qwen2-0.5B-Reward-DR-SIMU/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mamba413/Qwen2-0.5B-Reward-DR-SIMU/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- c301c6dd06d9dbf95373c72ba40812abb865d13660ccbf7850cacebb7155faad
- Size of remote file:
- 5.5 kB
- SHA256:
- 371a32de4a69f93a5ea100677eb436457b6e4e83f827b4c089b295c32299ef1a
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