4 ms·

You can currently play around with the 7B[0] and 14B[1] parameters models hosted in Hugging Face Spaces. [0] https://huggingface.co/spaces/BlinkDL/Raven-RWKV-7

You can currently play around with the 7B[0] and 14B[1] parameters models hosted in Hugging Face Spaces. [0] https://huggingface.co/spaces/BlinkDL/Raven-RWKV-7B https://huggingface.co/spaces/BlinkDL/Raven-RWKV-7B [1] https://huggingface.co/spaces/BlinkDL/ChatRWKV-gradio https://huggingface.co/spaces/BlinkDL/ChatRWKV-gradio

joshspankit 4y ago
This gave me a good chuckle. Thought I would share. (From ChatRWKV) Prompt: A website can be built in 10 simple steps Output: 1. Research 2. Research 3. Research 4. Research 5. Research 6. Research 7. Design 8. Design 9. Design 10. Design
aww_dang 4y ago
Also here: https://bellard.org/ts_server/ https://bellard.org/ts_server/
- tarruda 4y ago
  Somehow not surprised Bellard is also going to make an impact in AI/LLMs
  - synctext 4y ago
    > going to make an impact in AI/LLMs This seems to be made for mass parallelism. Question: Would this scale to 100 million of collaborating 4G/5G smartphones? We have operational federated learning code and decentralised learning code (trivial stochastic gradient descent). Application: simple learn-to-Rank based on ClickLogs like its 2005 [1]. Then you have a true decentralised Google. Would love to link RWKV to other pure decentralised tech. In the past we have build the first self-compiling Android app and first Android-to-Android P2P overlay network. Without any helper peers for carrier-grade NAT puncturing. My university systems lab lacks the size to keep up with the recent pace of innovation. [1] https://grouplens.org/beyond2005/full/pouwelse.pdf https://grouplens.org/beyond2005/full/pouwelse.pdf
  - mdp2021 4y ago
    > Somehow not surprised Bellard is also going to make an impact in AI[... ] He also wrote an engine: "LibNC: C Library for Tensor Manipulation" https://bellard.org/libnc/ https://bellard.org/libnc/ > [ ...]/LLMs That could be a wish come true. Edit: in fact, already one of his marks can be seen: «Larger models work optimally on lower cost GPUs (e.g. RTX 3090, RTX A6000) thanks to efficient quantization»
- ducktective 4y ago
  Man fears AGI AGI fears Fabrice Bellard
  - muttled 4y ago
    You're not lying. When I saw the site I thought "isn't that the dude who managed to emulate an entire PC in Javascript and boot Windows in a browser? Yep that's him."

joshspankit 4y ago

This gave me a good chuckle. Thought I would share. (From ChatRWKV) Prompt: A website can be built in 10 simple steps Output: 1. Research 2. Research 3. Research 4. Research 5. Research 6. Research 7. Design 8. Design 9. Design 10. Design

aww_dang 4y ago

Also here: https://bellard.org/ts_server/ https://bellard.org/ts_server/

tarruda 4y ago
Somehow not surprised Bellard is also going to make an impact in AI/LLMs
- synctext 4y ago
  > going to make an impact in AI/LLMs This seems to be made for mass parallelism. Question: Would this scale to 100 million of collaborating 4G/5G smartphones? We have operational federated learning code and decentralised learning code (trivial stochastic gradient descent). Application: simple learn-to-Rank based on ClickLogs like its 2005 [1]. Then you have a true decentralised Google. Would love to link RWKV to other pure decentralised tech. In the past we have build the first self-compiling Android app and first Android-to-Android P2P overlay network. Without any helper peers for carrier-grade NAT puncturing. My university systems lab lacks the size to keep up with the recent pace of innovation. [1] https://grouplens.org/beyond2005/full/pouwelse.pdf https://grouplens.org/beyond2005/full/pouwelse.pdf
- mdp2021 4y ago
  > Somehow not surprised Bellard is also going to make an impact in AI[... ] He also wrote an engine: "LibNC: C Library for Tensor Manipulation" https://bellard.org/libnc/ https://bellard.org/libnc/ > [ ...]/LLMs That could be a wish come true. Edit: in fact, already one of his marks can be seen: «Larger models work optimally on lower cost GPUs (e.g. RTX 3090, RTX A6000) thanks to efficient quantization»
ducktective 4y ago
Man fears AGI AGI fears Fabrice Bellard
- muttled 4y ago
  You're not lying. When I saw the site I thought "isn't that the dude who managed to emulate an entire PC in Javascript and boot Windows in a browser? Yep that's him."