Instructions to use Dahoas/gptneo-rm-static with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dahoas/gptneo-rm-static with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Dahoas/gptneo-rm-static")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Dahoas/gptneo-rm-static") model = AutoModelForSequenceClassification.from_pretrained("Dahoas/gptneo-rm-static", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2628ff6c5793d4cbd7adc419513d32b1d86a66db80f6f2fb459b016a61059eb
- Size of remote file:
- 5.36 GB
- SHA256:
- faeabe925b3702377e9211e73748d26c6f34a13f3a332ece9ea21fbc3b23e5d0
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