Instructions to use literid/contacts_socmedia_funetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use literid/contacts_socmedia_funetune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="literid/contacts_socmedia_funetune")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("literid/contacts_socmedia_funetune") model = AutoModelForSequenceClassification.from_pretrained("literid/contacts_socmedia_funetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d609c70215d2f5fdde9131fe3e82c7375d66ce4247d4d8b0cfebc379b7f0e52
- Size of remote file:
- 117 MB
- SHA256:
- 62fb4f6ab464abc41f905fd5a65518baf1fca3b50f1e40925c73b5898029fb4f
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