Instructions to use dusersad12/OrionLM-CheckpointRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/OrionLM-CheckpointRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dusersad12/OrionLM-CheckpointRepo")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dusersad12/OrionLM-CheckpointRepo") model = AutoModel.from_pretrained("dusersad12/OrionLM-CheckpointRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 93 Bytes
c376839 | 1 2 3 4 5 6 | {
"model_type": "bert",
"architectures": ["BertModel"],
"training_step": 700
}
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