Broadly distributed benefits
Model | GPU-RAM |
---|---|
GPT-3 | 350 GB |
Bloom | 352 GB |
Llama-2-70b | 140GB |
Falcon-40B | 80G |
starcoder | 31GB |
https://github.com/oobabooga/text-generation-webui
2. Additional Commercial Terms. If, on the Llama 2 version release date, the monthly active users of the products or services made available by or for Licensee, or Licensee’s affiliates, is greater than 700 million monthly active users in the preceding calendar month, you must request a license from Meta, which Meta may grant to you in its sole discretion, and you are not authorized to exercise any of the rights under this Agreement unless or until Meta otherwise expressly grants you such rights.
9.4. Where TII grants permission for You to make Hosting Use of the relevant Work, then for that purpose You shall be considered a Hosting User, and your use of Falcon 180B, the Work or Derivative Works shall be subject to the separate license granted by TII relating to that use.
https://opencompass.org.cn/leaderboard-llm
You will not use, copy, modify, merge, publish, distribute, reproduce, or create derivative works of the Software, in whole or in part, for any military, or illegal purposes.
You will not use the Software for any act that may undermine China's national security and national unity, harm the public interest of society, or infringe upon the rights and interests of human beings.
If you are commercially using the Materials, and your product or service has more than 100 million monthly active users, You shall request a license from Us. You cannot exercise your rights under this Agreement without our express authorization.
If you plan to use the Yi Series Models and Derivatives for Commercial Purposes, you should contact the Licensor in advance as specified in Section 7 of this Agreement named "Updates to the Agreement and Contact Information" and obtain written authorization from the Licensor.
Backend | Beschreibung | Support |
---|---|---|
Transformers | Huggingface FOSS-Library | GPU via pytorch,jax,Tensorflow |
llama.cpp | C++-implementierung von Transformern, eigene Quantifizierung | GPU Nvidia, Metal, ROCm |
ctransformers | C++ | Nvidia, |
exllama(v2) | Python, C++ und Cuda, rattenschnell | Nvidia, ROCm theoreitsch |
Die Modelle werden kleiner und
fähiger.
Multimodal wird zum Normalfall.
Beispiel: Qwen-VL
Multimodal wird zum Normalfall.
Und deutlich besser als GPT4-V
https://github.com/THUDM/CogVLM Apache Licence
Spezialsierungen wird üblich:
Damit wird auch Finetuning normal.
https://github.com/THUDM/CogVLM Apache Licence
https://slides.com/johann-peterhartmann/offeneai/