Text Classification
PEFT
Safetensors
Transformers
English
lora
qlora
process-reward-model
prm
clembench
game-playing
sequence-classification
trl
Instructions to use Diginyx/Qwen3.5-27B-prm-ep1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Diginyx/Qwen3.5-27B-prm-ep1 with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("/nfs/turbo/coe-chaijy-unreplicated/pre-trained-weights/Qwen3.5-27B") model = PeftModel.from_pretrained(base_model, "Diginyx/Qwen3.5-27B-prm-ep1") - Transformers
How to use Diginyx/Qwen3.5-27B-prm-ep1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Diginyx/Qwen3.5-27B-prm-ep1")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Diginyx/Qwen3.5-27B-prm-ep1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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