Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use mothy-08/drbftcm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mothy-08/drbftcm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mothy-08/drbftcm")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mothy-08/drbftcm") model = AutoModelForSequenceClassification.from_pretrained("mothy-08/drbftcm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d50c624deb7d2d11f87ddf27bf55c4578b33bd177cc77f8a17c03099ff3697d3
- Size of remote file:
- 5.78 kB
- SHA256:
- d6c7fff2fd98b3d65e88aae69aa32c8c853e176a042f41f585e9900feaf4a8aa
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