Feature Extraction
Transformers
PyTorch
Safetensors
fimhawkes
time-series
temporal-point-processes
hawkes-processes
scientific-ml
custom_code
Instructions to use FIM4Science/fim-pp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FIM4Science/fim-pp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="FIM4Science/fim-pp", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FIM4Science/fim-pp", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add model checkpoint (.pth)
Browse files- model-checkpoint.pth +3 -0
model-checkpoint.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:ca6607f15650cc0eb430d6a663ff539cd785640cf4db412ae09bcf63991a3ebd
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size 64581256
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