Text Classification
Transformers
Safetensors
English
qwen2
feature-extraction
prm
process-reward-model
reward model
math
hallucination-detection
custom_code
text-embeddings-inference
Instructions to use ZaandaTeika/Qwen2.5-Math-7B-SHARP-Step with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZaandaTeika/Qwen2.5-Math-7B-SHARP-Step with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ZaandaTeika/Qwen2.5-Math-7B-SHARP-Step", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ZaandaTeika/Qwen2.5-Math-7B-SHARP-Step", trust_remote_code=True) model = AutoModel.from_pretrained("ZaandaTeika/Qwen2.5-Math-7B-SHARP-Step", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from ZaandaTeika/Qwen2.5-Math-7B-SHARP-Step: direct link, hf CLI and curl.
- Browser
- Download file 1.74 kB
-
https://huggingface.co/ZaandaTeika/Qwen2.5-Math-7B-SHARP-Step/resolve/main/config.json
- Command line
-
hf download hf://ZaandaTeika/Qwen2.5-Math-7B-SHARP-Step/config.json
-
curl -L -o config.json https://huggingface.co/ZaandaTeika/Qwen2.5-Math-7B-SHARP-Step/resolve/main/config.json
1.74 kB
| { | |
| "architectures": [ | |
| "Qwen2ForProcessRewardModel" | |
| ], | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_qwen2_rm.Qwen2RMConfig", | |
| "AutoModel": "modeling_qwen2_rm.Qwen2ForProcessRewardModel", | |
| "AutoModelForSequenceClassification": "modeling_qwen2_rm.Qwen2ForProcessRewardModel", | |
| "AutoModelForTokenClassification": "modeling_qwen2_rm.Qwen2ForProcessRewardModel" | |
| }, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 151645, | |
| "hidden_act": "silu", | |
| "hidden_size": 3584, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 18944, | |
| "layer_types": [ | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention" | |
| ], | |
| "max_position_embeddings": 4096, | |
| "max_window_layers": 28, | |
| "model_type": "qwen2", | |
| "num_attention_heads": 28, | |
| "num_hidden_layers": 28, | |
| "num_key_value_heads": 4, | |
| "pad_token_id": 151643, | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": null, | |
| "rope_theta": 10000.0, | |
| "sliding_window": null, | |
| "tie_word_embeddings": false, | |
| "transformers_version": "4.57.6", | |
| "use_cache": false, | |
| "use_sliding_window": false, | |
| "vocab_size": 152064, | |
| "torch_dtype": "bfloat16", | |
| "num_labels": 2, | |
| "problem_type": "single_label_classification" | |
| } | |