Text Classification
Transformers
PyTorch
Safetensors
English
roberta
rlhf
reward-model
text-embeddings-inference
Instructions to use argilla/roberta-base-reward-model-falcon-dolly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use argilla/roberta-base-reward-model-falcon-dolly with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="argilla/roberta-base-reward-model-falcon-dolly")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("argilla/roberta-base-reward-model-falcon-dolly") model = AutoModelForSequenceClassification.from_pretrained("argilla/roberta-base-reward-model-falcon-dolly", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from argilla/roberta-base-reward-model-falcon-dolly: direct link, hf CLI and curl.
- Browser
- Download file 329 MB
-
https://huggingface.co/argilla/roberta-base-reward-model-falcon-dolly/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://argilla/roberta-base-reward-model-falcon-dolly/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/argilla/roberta-base-reward-model-falcon-dolly/resolve/main/pytorch_model.bin
329 MB
- Xet hash:
- c269b5f8163418d512b5091b1903c1d579676f0da7d68fd40fde4dfc99257030
- Size of remote file:
- 329 MB
- SHA256:
- 6ffee7e2a3383d3342f9193d63820683d8af07b39143f98c7084b1a1f27049c5
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