Instructions to use microsoft/bloom-deepspeed-inference-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/bloom-deepspeed-inference-fp16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="microsoft/bloom-deepspeed-inference-fp16")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("microsoft/bloom-deepspeed-inference-fp16") model = AutoModel.from_pretrained("microsoft/bloom-deepspeed-inference-fp16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de701d269b63b580bc97fcd55468d5d9709d06c7ca21acd5380a08eade728537
- Size of remote file:
- 5.55 GB
- SHA256:
- 581a096bc97d334fc40fe36683943ad0286876b3ccec7bea7cb1e12193cdcd96
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