Hugging Face's transformers is a popular Python library for model training and inference.
It may be possible to infer some information from the uses of well-known functions and classes like AutoModelForCausalLM and AutoTokenizer.
For example, from the code
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "Qwen/Qwen3-30B-A3B-Thinking-2507"
# load the tokenizer and the model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype="auto",
device_map="auto"
)
We can infer that this model uses tokenizer from "Qwen/Qwen3-30B-A3B-Thinking-2507".
More information could be obtain from tokenizer_config.json and config.json inside model repo on Hugging Face.
Hugging Face's transformers is a popular Python library for model training and inference.
It may be possible to infer some information from the uses of well-known functions and classes like
AutoModelForCausalLMandAutoTokenizer.For example, from the code
We can infer that this model uses tokenizer from "Qwen/Qwen3-30B-A3B-Thinking-2507".
More information could be obtain from
tokenizer_config.jsonandconfig.jsoninside model repo on Hugging Face.