Text Classification
Transformers
Safetensors
Ganda
English
gemma3_text
luganda
reward-model
reward-modeling
rlhf
grpo
dpo
gemma
gemma3
translation-quality
africa
text-embeddings-inference
Instructions to use CraneAILabs/luganda-reward-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CraneAILabs/luganda-reward-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CraneAILabs/luganda-reward-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CraneAILabs/luganda-reward-model") model = AutoModelForSequenceClassification.from_pretrained("CraneAILabs/luganda-reward-model") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "boi_token": "<start_of_image>", | |
| "bos_token": "<bos>", | |
| "clean_up_tokenization_spaces": false, | |
| "eoi_token": "<end_of_image>", | |
| "eos_token": "<end_of_turn>", | |
| "image_token": "<image_soft_token>", | |
| "is_local": false, | |
| "mask_token": "<mask>", | |
| "max_length": null, | |
| "model_max_length": 32768, | |
| "model_specific_special_tokens": { | |
| "boi_token": "<start_of_image>", | |
| "eoi_token": "<end_of_image>", | |
| "image_token": "<image_soft_token>" | |
| }, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "<pad>", | |
| "pad_token_type_id": 0, | |
| "padding_side": "left", | |
| "processor_class": "Gemma3Processor", | |
| "sp_model_kwargs": null, | |
| "spaces_between_special_tokens": false, | |
| "stride": 0, | |
| "tokenizer_class": "GemmaTokenizer", | |
| "truncation_side": "right", | |
| "truncation_strategy": "longest_first", | |
| "unk_token": "<unk>", | |
| "use_default_system_prompt": false | |
| } | |