Text Classification
Transformers
Safetensors
llama
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use tsessk/llm-course-hw2-reward-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tsessk/llm-course-hw2-reward-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tsessk/llm-course-hw2-reward-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tsessk/llm-course-hw2-reward-model") model = AutoModelForSequenceClassification.from_pretrained("tsessk/llm-course-hw2-reward-model") - Notebooks
- Google Colab
- Kaggle
File size: 704 Bytes
1558846 | 1 2 3 4 5 6 7 8 9 | 2025-03-05 14:26:41,014 DEBUG root Loaded Command Group: ['gcloud', 'config']
2025-03-05 14:26:41,057 DEBUG root Loaded Command Group: ['gcloud', 'config', 'set']
2025-03-05 14:26:41,059 DEBUG root Running [gcloud.config.set] with arguments: [SECTION/PROPERTY: "component_manager/disable_update_check", VALUE: "true"]
2025-03-05 14:26:41,060 INFO ___FILE_ONLY___ Updated property [component_manager/disable_update_check].
2025-03-05 14:26:41,061 DEBUG root Chosen display Format:default
2025-03-05 14:26:41,061 INFO root Display format: "default"
2025-03-05 14:26:41,062 DEBUG root SDK update checks are disabled.
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