Instructions to use Xuanda/test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Xuanda/test-model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Xuanda/test-model") model = AutoModel.from_pretrained("Xuanda/test-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload LSTM_LM
Browse files- config.json +0 -1
- pytorch_model.bin +1 -1
config.json
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{
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"_name_or_path": "Xuanda/test-model",
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"architectures": [
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"LSTM_LM"
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],
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{
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"architectures": [
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"LSTM_LM"
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],
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 3913
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version https://git-lfs.github.com/spec/v1
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oid sha256:ac01b40cf73b62eefd239967ae9fece2eea4f07975cf608fb9b9a59112e5602d
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size 3913
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