Text Classification
Transformers
Safetensors
qwen3
text-generation
code-reward-model
reward-model
grpo
selection
best-of-n
rlhf
awq
awq-int4
quantized
4bit
noesis
dhcf-fno
apache-2.0
text-embeddings-inference
4-bit precision
Instructions to use AMAImedia/CodeRM-GRPO-Selection-8B-NOESIS-AWQ-INT4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AMAImedia/CodeRM-GRPO-Selection-8B-NOESIS-AWQ-INT4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AMAImedia/CodeRM-GRPO-Selection-8B-NOESIS-AWQ-INT4")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AMAImedia/CodeRM-GRPO-Selection-8B-NOESIS-AWQ-INT4") model = AutoModelForCausalLM.from_pretrained("AMAImedia/CodeRM-GRPO-Selection-8B-NOESIS-AWQ-INT4") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_from_model_config": true, | |
| "do_sample": true, | |
| "eos_token_id": 151645, | |
| "pad_token_id": 151654, | |
| "transformers_version": "5.8.1" | |
| } | |