Instructions to use clem/autonlp-test3-2101787 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clem/autonlp-test3-2101787 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="clem/autonlp-test3-2101787")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("clem/autonlp-test3-2101787") model = AutoModelForSequenceClassification.from_pretrained("clem/autonlp-test3-2101787", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from clem/autonlp-test3-2101787: direct link, hf CLI and curl.
- Browser
- Download file 263 MB
-
https://huggingface.co/clem/autonlp-test3-2101787/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://clem/autonlp-test3-2101787/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/clem/autonlp-test3-2101787/resolve/main/pytorch_model.bin
263 MB
- Xet hash:
- cb6bb23f92d719b0ecf8036d653878e7078b838b4c25f0049e59be2218368ec3
- Size of remote file:
- 263 MB
- SHA256:
- 119636cd350199d345976893f80202f23942dd210ba407adb4312bfcb8c96ace
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