Instructions to use Forturne/instruct_0.5b_ret with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Forturne/instruct_0.5b_ret with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Forturne/instruct_0.5b_ret")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Forturne/instruct_0.5b_ret") model = AutoModel.from_pretrained("Forturne/instruct_0.5b_ret", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a43a35b7e78b334de031ac65399f9fcff270842c571b0c713c71d57d2c5830c
- Size of remote file:
- 11.4 MB
- SHA256:
- fd8e691229b8563dd858d9b56b1559f8b9778effadb03cee5744ecccc1701241
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