Instructions to use Forturne/instruct_ret with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Forturne/instruct_ret with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Forturne/instruct_ret", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Forturne/instruct_ret", trust_remote_code=True) model = AutoModel.from_pretrained("Forturne/instruct_ret", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e55d67b50c008f8ef0ddbbf5a4a47c948d35dc3bdda3b7191b24e74d0fb32bc
- Size of remote file:
- 3.09 GB
- SHA256:
- e4349940735f8db3608b15a602b23fd24ca8696eec53b4678d26519a0924958a
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