Instructions to use hf-tiny-model-private/tiny-random-LukeForSequenceClassification 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-LukeForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-LukeForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-LukeForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-LukeForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-LukeForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 6.79 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-LukeForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-LukeForSequenceClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-LukeForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
6.79 MB
- Xet hash:
- ffa86e2234bdc0ffe09e134bb5aa3cbb73f43586f1166797d40e1a767b8bfc70
- Size of remote file:
- 6.79 MB
- SHA256:
- 5882f0c283e27a4bdf2be541d530187cc89f204d3b1166a2f3adbc75ec8cb5b6
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