Text Classification
Transformers
Safetensors
English
deberta-v2
reward-model
scpo
cultural-alignment
canada
text-embeddings-inference
Instructions to use MulticulturalAlignment/scpo-reward-model-canada with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MulticulturalAlignment/scpo-reward-model-canada with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MulticulturalAlignment/scpo-reward-model-canada")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MulticulturalAlignment/scpo-reward-model-canada") model = AutoModelForSequenceClassification.from_pretrained("MulticulturalAlignment/scpo-reward-model-canada", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checksums.json from MulticulturalAlignment/scpo-reward-model-canada: direct link, hf CLI and curl.
- Browser
- Download file 1.6 kB
-
https://huggingface.co/MulticulturalAlignment/scpo-reward-model-canada/resolve/main/checksums.json
- Command line
-
hf download hf://MulticulturalAlignment/scpo-reward-model-canada/checksums.json
-
curl -L -o checksums.json https://huggingface.co/MulticulturalAlignment/scpo-reward-model-canada/resolve/main/checksums.json
1.6 kB
| { | |
| "LICENSE": "871f503d007714998cf2b9d35d73563b856182070552156771260aa3d12d953e", | |
| "README.md": "bae2e3d0fd6ac169991454467bbe7f08dd92bf66f24f221e2b39c47a8950b272", | |
| "added_tokens.json": "dc046d04c9b0ada7ae6f1dc89c465801799acdf0c9a6aab8c15a1b2d5ca4e91f", | |
| "config.json": "d88248219ef56b7227b25161fe83bfc1f949d77032367525b372270ef80bef17", | |
| "model.safetensors": "aa23ee2ae72319bcc6351cd800c413a320856483208fc09f7e447351ba868583", | |
| "provenance.json": "fd6291ee5bc555a8abbe283f6e81a7fcfe153cb5fbc18ccbc1a0d8b4e7c2a2c8", | |
| "release-settings.json": "df34196ae4709cef88574e10e06b2bd6e940a7881d4ee2428219ac75c75ed4f6", | |
| "requirements-pw-lock.txt": "abe2e55884496b23fc4206efbf563edc7cfc615ef37189851f6f442454e3e8bc", | |
| "special_tokens_map.json": "63cd5b53789b3b5ae2c3d7aa377bcba1557ff0b41dc69ce07b94350ea32291c2", | |
| "spm.model": "c679fbf93643d19aab7ee10c0b99e460bdbc02fedf34b92b05af343b4af586fd", | |
| "tokenizer.json": "b8d055f68ab07e04ecdeacf0bf506d578d826d2682b4709c94899a2f3556f583", | |
| "tokenizer_config.json": "2c9737294d56f67d6122507ce309dfb8dd98221a73ed8315db8f9b07cf1988fa", | |
| "validation.json": "f8ec56e8a9fa315675301294d15e14f753aa22480629349f4c31d2cff427edde", | |
| "reproduction/our_data_collator.py": "67c1b081e7886ed8a5747abe7612ff255f0043d8c3d59ef64bb774db12518c79", | |
| "reproduction/our_inverse_reward_trainer.py": "b41fc006ae62dfdd5553217cdb231c35d45c80dd5437f3f7c70ce006f59835a1", | |
| "reproduction/our_reward_trainer.py": "35aea8a2f4b30f51e5427b61418698d69528b868fd7b35abad7132508d092ab3", | |
| "reproduction/preferences.py": "16642fdfa0c817ca2b0ce33600d6478535f2994bef5c4f00d0d7b7227026b72e" | |
| } | |