Instructions to use AnonymousSub/output_FPDM_Cus_RL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousSub/output_FPDM_Cus_RL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="AnonymousSub/output_FPDM_Cus_RL")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("AnonymousSub/output_FPDM_Cus_RL") model = AutoModelForQuestionAnswering.from_pretrained("AnonymousSub/output_FPDM_Cus_RL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed622e4c15e4d830f610b58b73bbcbdd16659fa59c3996cb5eb8ec799a916cc4
- Size of remote file:
- 1.42 GB
- SHA256:
- 8ae7253f51fae5122257ffbdd139745c2a0d72fea84a5f27c6a7ae518a5ec33c
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