Instructions to use LiukG/gut_1024-finetuned-lora-NT-v2-100m-ms with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LiukG/gut_1024-finetuned-lora-NT-v2-100m-ms with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LiukG/gut_1024-finetuned-lora-NT-v2-100m-ms", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LiukG/gut_1024-finetuned-lora-NT-v2-100m-ms", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("LiukG/gut_1024-finetuned-lora-NT-v2-100m-ms", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1aae3eb90fa0c83f559cc542c122afc5c6b1608ff75e8973d5b149dd5b358119
- Size of remote file:
- 4.98 kB
- SHA256:
- 713b854daf65b07bd2850d5de03dcc3ad946773dd0620800263fb72c4b5b20ad
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