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
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": null, | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "errors": "replace", | |
| "is_local": true, | |
| "local_files_only": false, | |
| "model_max_length": 40960, | |
| "pad_token": "<|vision_pad|>", | |
| "padding_side": "left", | |
| "split_special_tokens": false, | |
| "tokenizer_class": "Qwen2Tokenizer", | |
| "unk_token": null | |
| } | |