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 tokenizer.model from HuggingFaceH4/tiny-random-LlamaForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 500 kB
-
https://huggingface.co/HuggingFaceH4/tiny-random-LlamaForSequenceClassification/resolve/0960e9816e59a162c8b65f47d919f3e293db082c/tokenizer.model
- Command line
-
hf download hf://HuggingFaceH4/tiny-random-LlamaForSequenceClassification@0960e9816e59a162c8b65f47d919f3e293db082c/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/HuggingFaceH4/tiny-random-LlamaForSequenceClassification/resolve/0960e9816e59a162c8b65f47d919f3e293db082c/tokenizer.model
500 kB
- Xet hash:
- 91bf184ab12793d0754344f9095332759432e666320cc6c07f637af50e36db6f
- Size of remote file:
- 500 kB
- SHA256:
- 9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
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