Instructions to use sybk/hk_backward_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sybk/hk_backward_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sybk/hk_backward_v2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sybk/hk_backward_v2") model = AutoModel.from_pretrained("sybk/hk_backward_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0bd04ab2348570b44e59da9392d10f4f5ea54e0a8023d1e813c465884e25165
- Size of remote file:
- 513 MB
- SHA256:
- a059ed8341e85b92222fdaedec54c7f4d4b5f83dd6fe282d37ce6b4605ce009f
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