Instructions to use Wesleythu/init_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wesleythu/init_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Wesleythu/init_model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Wesleythu/init_model") model = AutoModel.from_pretrained("Wesleythu/init_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| The model is trained based on LLAMA 2. Please adhere to license. | |
| We use a subset of TULU v2 instruction tuning corpus to train the model. | |
| We use a subset of TULU v2 instruction tuning corpus to train the model. | |