Instructions to use hf-internal-testing/tiny-random-SplinterModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SplinterModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-SplinterModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SplinterModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-SplinterModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-SplinterModel: direct link, hf CLI and curl.
- Browser
- Download file 3.93 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-SplinterModel/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-SplinterModel@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-SplinterModel/resolve/refs%2Fpr%2F1/model.safetensors
3.93 MB
- Xet hash:
- 2df335e10a87c05e11af33f4eefd9b5f3dd2cdbf029a2ccddb3319775d575192
- Size of remote file:
- 3.93 MB
- SHA256:
- 63e02a19b4a6aacd2a23a4bfacdb7ac47d3bec9143253b7c02111af9f45e9bd2
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