Instructions to use jdchang/test_rm_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jdchang/test_rm_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jdchang/test_rm_small", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jdchang/test_rm_small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 128000, | |
| "eos_token_id": 128009, | |
| "transformers_version": "4.43.4", | |
| "use_cache": false | |
| } | |