Instructions to use HuggingFaceH4/tiny-random-LlamaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HuggingFaceH4/tiny-random-LlamaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HuggingFaceH4/tiny-random-LlamaForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HuggingFaceH4/tiny-random-LlamaForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("HuggingFaceH4/tiny-random-LlamaForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from HuggingFaceH4/tiny-random-LlamaForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 2.09 MB
-
https://huggingface.co/HuggingFaceH4/tiny-random-LlamaForSequenceClassification/resolve/0960e9816e59a162c8b65f47d919f3e293db082c/pytorch_model.bin
- Command line
-
hf download hf://HuggingFaceH4/tiny-random-LlamaForSequenceClassification@0960e9816e59a162c8b65f47d919f3e293db082c/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/HuggingFaceH4/tiny-random-LlamaForSequenceClassification/resolve/0960e9816e59a162c8b65f47d919f3e293db082c/pytorch_model.bin
2.09 MB
- Xet hash:
- a595445d51d3519fe03b4b4f64923c434e4c72319e41dea3ed3014e98073e14c
- Size of remote file:
- 2.09 MB
- SHA256:
- 8b723928ef44846c215bcad4a10d305cf2fb28d1b1d65f03f1907698ce463e75
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