BLOOM
BLOOM is a 176B parameter multilingual LLM created through open collaboration, trained on 46 natural and 13 programming languages, offering open access at GPT-3 scale.
3 Steps
- 1
Explore BLOOM's Capabilities: Visit the Hugging Face BLOOM demo to interact with the model and test its multilingual capabilities. Experiment with different prompts in various languages to observe its responses.
- 2
Access BLOOM via Hugging Face Transformers: Use the Hugging Face Transformers library to load and run BLOOM. Install the library if you haven't already, then use the `AutoModelForCausalLM` and `AutoTokenizer` classes to load the model and tokenizer.
- 3
Generate Text with BLOOM: Use the loaded model and tokenizer to generate text. Encode your input prompt using the tokenizer, pass it to the model, and decode the output to get the generated text.
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