Instructions to use hf-tiny-model-private/tiny-random-XLMModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-XLMModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-XLMModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-XLMModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-XLMModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from hf-tiny-model-private/tiny-random-XLMModel: direct link, hf CLI and curl.
- Browser
- Download file 4.28 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-XLMModel/resolve/main/tf_model.h5
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-XLMModel/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/hf-tiny-model-private/tiny-random-XLMModel/resolve/main/tf_model.h5
4.28 MB
- Xet hash:
- 29043ca35addaccf4fa17aef678851e1c8e848d3c99b2b2da743e1c96f127c7f
- Size of remote file:
- 4.28 MB
- SHA256:
- 37bdfc34bd4a1f3320d7623b73bcef36783285597718e31a3186206968797769
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