Instructions to use Jennny/eng_rm_1e5_700 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jennny/eng_rm_1e5_700 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jennny/eng_rm_1e5_700", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jennny/eng_rm_1e5_700") model = AutoModelForSequenceClassification.from_pretrained("Jennny/eng_rm_1e5_700", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fdef1a9352226e0ff9e4dd5c8ca6a8749be58838e49c4a8f6f197adf4ff42669
- Size of remote file:
- 30 GB
- SHA256:
- f430e35966d1db5f1af55ed96b3a4eea291637d25eee6a4c73245015aa5e1b68
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