Instructions to use aloeme/llm-course-hw2-reward-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aloeme/llm-course-hw2-reward-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aloeme/llm-course-hw2-reward-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aloeme/llm-course-hw2-reward-model") model = AutoModelForSequenceClassification.from_pretrained("aloeme/llm-course-hw2-reward-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
ca7581c | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:cfc357c00746b793213586c6432a241559c65018a5c7256ef5f0bd6c216a3183
size 538092792
|