Automatic Speech Recognition
Transformers
Safetensors
English
Chinese
glmasr
text2text-generation
Eval Results
Instructions to use ConsHein/GLM-ASR-Nano-2512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ConsHein/GLM-ASR-Nano-2512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ConsHein/GLM-ASR-Nano-2512")# Load model directly from transformers import AutoProcessor, AutoModelForSeq2SeqLM processor = AutoProcessor.from_pretrained("ConsHein/GLM-ASR-Nano-2512") model = AutoModelForSeq2SeqLM.from_pretrained("ConsHein/GLM-ASR-Nano-2512") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "clean_up_tokenization_spaces": false, | |
| "do_lower_case": false, | |
| "eos_token": "<|endoftext|>", | |
| "extra_special_tokens": [ | |
| "<|endoftext|>", | |
| "[MASK]", | |
| "[gMASK]", | |
| "[sMASK]", | |
| "<sop>", | |
| "<eop>", | |
| "<|system|>", | |
| "<|user|>", | |
| "<|assistant|>", | |
| "<|observation|>", | |
| "<|begin_of_image|>", | |
| "<|end_of_image|>", | |
| "<|begin_of_video|>", | |
| "<|end_of_video|>", | |
| "<|pad|>", | |
| "<|begin_of_audio|>", | |
| "<|end_of_audio|>" | |
| ], | |
| "is_local": false, | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 65536, | |
| "model_specific_special_tokens": {}, | |
| "pad_token": "<|endoftext|>", | |
| "padding_side": "left", | |
| "processor_class": "GlmAsrProcessor", | |
| "remove_space": false, | |
| "tokenizer_class": "TokenizersBackend" | |
| } | |