Instructions to use hf-tiny-model-private/tiny-random-XmodForSequenceClassification 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-XmodForSequenceClassification 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-XmodForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-XmodForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-XmodForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-XmodForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 32.3 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-XmodForSequenceClassification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-XmodForSequenceClassification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-XmodForSequenceClassification/resolve/main/pytorch_model.bin
32.3 MB
- Xet hash:
- 9a8d737a297edc1e1d4cb22a98aa69b130a637884671fd2ca2f4c0cada758294
- Size of remote file:
- 32.3 MB
- SHA256:
- c6a1d2a2063acc37441b5117929a2476f20817e3cd98de7342bd3ccf871f69da
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