Instructions to use hunoutl/bloomchat-deepspeed-inference-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hunoutl/bloomchat-deepspeed-inference-fp16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hunoutl/bloomchat-deepspeed-inference-fp16")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hunoutl/bloomchat-deepspeed-inference-fp16") model = AutoModel.from_pretrained("hunoutl/bloomchat-deepspeed-inference-fp16") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
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- 5.55 GB xet
- 4.93 GB xet
- 5.14 GB xet
- 5.55 GB xet
- 5.5 GB xet
- 5.55 GB xet
- 5.4 GB xet
- 5.55 GB xet
- 5.55 GB xet
- 4.93 GB xet
- 5.14 GB xet
- 5.55 GB xet
- 5.5 GB xet
- 5.55 GB xet
- 5.4 GB xet
- 5.55 GB xet
- 5.55 GB xet
- 4.93 GB xet
- 5.14 GB xet
- 5.55 GB xet