Instructions to use Akash751/banglabert-code-mixed-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Akash751/banglabert-code-mixed-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Akash751/banglabert-code-mixed-emotion", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Akash751/banglabert-code-mixed-emotion") model = AutoModelForSequenceClassification.from_pretrained("Akash751/banglabert-code-mixed-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c27d5799c96c95f4d7317e54a1d3ca73097713de43339635447678c7d527672
- Size of remote file:
- 1.47 kB
- SHA256:
- 370aedac1e686f93877ba544700b4f0e3e90cb7211c6830bbe0ade3b3dfa8530
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