Text Classification
Transformers
Safetensors
English
Chinese
qwen2
feature-extraction
reward model
custom_code
text-embeddings-inference
Instructions to use Qwen/Qwen2.5-Math-PRM-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Qwen/Qwen2.5-Math-PRM-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Qwen/Qwen2.5-Math-PRM-7B", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-Math-PRM-7B", trust_remote_code=True) model = AutoModel.from_pretrained("Qwen/Qwen2.5-Math-PRM-7B", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
"<extra_0>" is not special token ? I got 5 token_ids ,is it right?
#4
by ShelterW - opened
tokenizer.encode("<extra_0>")
[27,15460,62,15,29]
tokenizer.decode([34139]) = ']<'
tokenizer.decode([27]) = '<'
is bug
suggest use
"\n<extra_0>"
or
".<extra_0>"
Which tokenizer are you using? In the tokenizer config of this file, '<extra_0>' is a special token.
"151651": {
"content": "<extra_0>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
yeah, my mistake
ShelterW changed discussion status to closed
suggest use
"\n<extra_0>"or
``