Summarization
Transformers
Safetensors
English
phi
text-generation
arxiv
custom_code
text-generation-inference
Instructions to use AlgorithmicResearchGroup/phi-biology with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlgorithmicResearchGroup/phi-biology with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="AlgorithmicResearchGroup/phi-biology", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AlgorithmicResearchGroup/phi-biology", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("AlgorithmicResearchGroup/phi-biology", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03f84163f7949db4c02bf3ee68144ab5632d3880988d7e6fbb75ddb4d94dcc2f
- Size of remote file:
- 2.84 GB
- SHA256:
- 9628909081b67a3dfaf6711ba9343ac585e75240ae6e41f6a9ba8b180dda5db4
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