Instructions to use chendelong/ChatGLM-PSP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chendelong/ChatGLM-PSP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="chendelong/ChatGLM-PSP", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("chendelong/ChatGLM-PSP", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.527dab8
-
Create README.md
<div align="center"> ## 🎙 [Towards Joint Modeling of Dialogue Response and Speech Synthesis based on Large Language Model](https://huggingface.co/papers/2309.11000) [Xinyu Zhou (周欣宇)](https://www.linkedin.com/in/xinyu-zhou2000/), [Delong Chen (陈德龙)](https://chendelong.world/), [Yudong Chen (陈玉东)](https://rwxy.cuc.edu.cn/2019/0730/c5134a133504/pagem.htm) [ArXiv](https://arxiv.org/abs/2309.11000) | [Poster](doc/YFRSW_Poster.pdf) | [Notebook](prosody_prediction.ipynb) | [Github](https://github.com/XinyuZhou2000/Spoken-Dialogue) </div> This project explores the potential of constructing an AI spoken dialogue system that *"thinks how to respond"* and *"thinks how to speak"* simultaneously, which more closely aligns with the human speech production process compared to the current cascade pipeline of independent chatbot and Text-to-Speech (TTS) modules. We hypothesize that *Large Language Models (LLMs)* with billions of parameters possess significant speech understanding capabilities…2d895f3 -
Create README.md
<div align="center"> ## 🎙 [Towards Joint Modeling of Dialogue Response and Speech Synthesis based on Large Language Model](https://huggingface.co/papers/2309.11000) [Xinyu Zhou (周欣宇)](https://www.linkedin.com/in/xinyu-zhou2000/), [Delong Chen (陈德龙)](https://chendelong.world/), [Yudong Chen (陈玉东)](https://rwxy.cuc.edu.cn/2019/0730/c5134a133504/pagem.htm) [ArXiv](https://arxiv.org/abs/2309.11000) | [Poster](doc/YFRSW_Poster.pdf) | [Notebook](prosody_prediction.ipynb) | [Github](https://github.com/XinyuZhou2000/Spoken-Dialogue) </div> This project explores the potential of constructing an AI spoken dialogue system that *"thinks how to respond"* and *"thinks how to speak"* simultaneously, which more closely aligns with the human speech production process compared to the current cascade pipeline of independent chatbot and Text-to-Speech (TTS) modules. We hypothesize that *Large Language Models (LLMs)* with billions of parameters possess significant speech…f6523e1
-
Upload 15 files
647849e -
initial commit
cf497fc