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:
- f67ade29c0c032609d08965e6c4dfece54ee15af66613d113b6a1ee637684e44
- Size of remote file:
- 4.73 GB
- SHA256:
- a35a45360c5084190d572b095133dcc71dedfd2e7408cedeed2effe1c128c529
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