Summarization
Transformers
Safetensors
English
phi
text-generation
arxiv
custom_code
text-generation-inference
Instructions to use AlgorithmicResearchGroup/phi-physics with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlgorithmicResearchGroup/phi-physics 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-physics", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AlgorithmicResearchGroup/phi-physics", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("AlgorithmicResearchGroup/phi-physics", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Commit History
Upload PhiForCausalLM 0bb9ff7
Update README.md 1628562
Update README.md 6163030
Update README.md 1e4ac8b
Create requirements.txt e8fee09
Create handler.py 509f4a0
Create configuration_mixformer_sequential.py f5cce54
Upload tokenizer fc4b5c8
Upload PhiForCausalLM 4a5271c
Upload tokenizer e83d584
Upload model ea2c08d
initial commit 07f35b4
Matthew Kenney commited on