Text Classification
Transformers
Safetensors
llama
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use zzzhr97/TRM-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zzzhr97/TRM-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zzzhr97/TRM-8B")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zzzhr97/TRM-8B") model = AutoModelForSequenceClassification.from_pretrained("zzzhr97/TRM-8B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Improve model card: add paper link, metadata, and sample usage
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community science team. This PR aims to improve the model card for TRM-8B by:
- Linking the model to its original paper: Characterizing, Evaluating, and Optimizing Complex Reasoning.
- Updating the metadata with the correct
pipeline_tagandlicense. - Adding a sample usage section extracted from the official GitHub repository to demonstrate how to score reasoning traces.
- Including the bibtex citation for the paper.
zzzhr97 changed pull request status to merged