Text Classification
Transformers
Safetensors
llama
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use RLHF-And-Friends/TLDR-Llama-3.2-3B-SmallSFT-RM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RLHF-And-Friends/TLDR-Llama-3.2-3B-SmallSFT-RM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RLHF-And-Friends/TLDR-Llama-3.2-3B-SmallSFT-RM")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RLHF-And-Friends/TLDR-Llama-3.2-3B-SmallSFT-RM") model = AutoModelForSequenceClassification.from_pretrained("RLHF-And-Friends/TLDR-Llama-3.2-3B-SmallSFT-RM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0760c0a2895eef2905a88c61d7afc3e8896ab7d3b0e17349f92befdc20c703c
- Size of remote file:
- 6.03 kB
- SHA256:
- ed7c99c9e011259b40b02480bec8fbfeaa07ec2c26f7cbb8f107f7465c92c576
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