Instructions to use chargoddard/chai-rm-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chargoddard/chai-rm-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chargoddard/chai-rm-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chargoddard/chai-rm-test") model = AutoModelForSequenceClassification.from_pretrained("chargoddard/chai-rm-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:385bac5584b684094a9037d1623c44bef75718ef2c4c39c26527f4001f454403
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size 497780432
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