Instructions to use AnonymousSub/FPDM_Cus_RL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousSub/FPDM_Cus_RL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AnonymousSub/FPDM_Cus_RL")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AnonymousSub/FPDM_Cus_RL") model = AutoModel.from_pretrained("AnonymousSub/FPDM_Cus_RL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb52698cc71b6babd55dd0cb9750ecf196c3662ea5786cc6b61086dbec9d8b12
- Size of remote file:
- 1.42 GB
- SHA256:
- b5372167075207842d8ee29731b6f4fb941adf6753e46b54ee1cc42a28e979ae
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