Instructions to use mlovelli/chatbot-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlovelli/chatbot-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mlovelli/chatbot-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mlovelli/chatbot-model") model = AutoModelForSequenceClassification.from_pretrained("mlovelli/chatbot-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a678fd7a812835da94719c4b294bb8436cd96838e38493c828b8c202739f077
- Size of remote file:
- 738 MB
- SHA256:
- 0365b0074f071930e4a49f57431f368d867867d02c2da8693d58133f35774ddc
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