Instructions to use 1231czx/uf_rm_llama3_it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 1231czx/uf_rm_llama3_it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="1231czx/uf_rm_llama3_it")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("1231czx/uf_rm_llama3_it") model = AutoModelForSequenceClassification.from_pretrained("1231czx/uf_rm_llama3_it", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c679f6273e730c1d29f87088adb9fafae2ecfeceb00420549f8db67590b5f0ae
- Size of remote file:
- 17.2 MB
- SHA256:
- 6bf0b47b65db9d1cbd1b400139006fd14267d16e3ead1728c6c202087e258041
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