Instructions to use michahu8/pythia-160m-sd-500-c4-10k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michahu8/pythia-160m-sd-500-c4-10k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="michahu8/pythia-160m-sd-500-c4-10k")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("michahu8/pythia-160m-sd-500-c4-10k") model = AutoModel.from_pretrained("michahu8/pythia-160m-sd-500-c4-10k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
See https://github.com/michahu/pre-pretraining for more information.
Usage:
model = AutoModel.from_pretrained('michahu8/pythia-160m-sd-500-c4-10k')
tokenizer = AutoTokenizer.from_pretrained('EleutherAI/pythia-160m')
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