Instructions to use hf-internal-testing/tiny-random-gpt_neo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-gpt_neo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-gpt_neo")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-gpt_neo") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-gpt_neo") - Notebooks
- Google Colab
- Kaggle
Upload ONNX weights
#2
by Xenova HF Staff - opened
- onnx/model.onnx +3 -0
onnx/model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:d3a8cebb88c4d7ecca8970c1d9aa8e08952ba0a40fd7eac0fd23f20bbe26b8df
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size 1001753
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