ggerganov

8 ms·

31.
by ggerganov 3y ago
Just make the same Javscript that provides random moves, make it play 100 games and take the average score. Then do the same using GPT and compare the scores. Anything else is just cherry-picking
32.
by ggerganov 3y ago
I just played 2 games randomly pressing all arrow keys with closed eyes and got a score of ~1100 in the first game and 1468 in the second game. OP's AI agent scored 1348
33.
by ggerganov 3y ago
Cool demo Just want to point out that we are actively working on improving the quantization accuracy / performance of ggml [0]. We already have promising results that are yet to be ported to the WASM code path, so hopefully such type o
34.
by ggerganov 4y ago
Heh, things seem to be moving in this direction, but I think it's still a very long way to go. But who knows - the amount of contributions to the project keep growing. I guess when we have a solid foundation for LLM inference we can th
35.
by ggerganov 4y ago
Hey liuliu, would love if you join the project when you find the time - your work is really inspiring!
36.
by ggerganov 4y ago
I expect LibNC will be better in every aspect: performance, accuracy, determinism. But hopefully with time we will close the gap.
37.
by ggerganov 4y ago
Very inspiring stuff! I hope one day we get to see the magic behind libnc.
38.
by ggerganov 4y ago
"Clean Code, Horrible Performance" :)
39.
by ggerganov 4y ago
Our investigations indicate that it might not be possible to achieve ANE performance improvement over CPU for LLM Decoder inference with batch size of 1 [0]. Just to make it clear - I'm no expert in Core ML / ANE, so these conclus
40.
by ggerganov 4y ago
I haven't run the original PyTorch model not a single time! I just look at the code and port it. I don't have the hardware to run it.
41.
by ggerganov 4y ago
It currently uses only the CPU via ARM NEON intrinsics - no GPU, no ANE and no Apple Accelerate. Plan is in the future to utilize respective SIMD intrinsics for other architectures (AVX, WASM SIMD, etc) and also add other more accurate quan
42.
Appler: Apple ][ emulator for IBM PC, written in 8088 assembly(github.com)
171 points by ggerganov 4y ago|47 comments
43.
by ggerganov 4y ago
Recently I made some progress on efficiently detecting short voice commands (wake words) on RPi4 [0]. Checkout the "command" example in whisper.cpp and it's "Guided mode" operation. There are additional improvements
44.
by ggerganov 4y ago
Yes - more of this please :) Tangentially related and discussed in the past on HN: File transfer via color barcodes and a phone camera [0] https://news.ycombinator.com/item?id=25459501 [1] https://github.com&#x2F
45.
by ggerganov 4y ago
In 1991, the Bulgarian national television aired a prank that the nuclear plant in the country has exploded [0]. Initially, a lot of people were very scared and believed that it really happened. [0] https://www.nytimes.com&#x2F
46.
by ggerganov 4y ago
Great project! I used it to create a Twitter bot that posts Doom videos (@tweet2doom). Back then it didn't have sound support, but it is great to see that it supports it now. Edit: I just realised it uses the modifications that I made
47.
by ggerganov 4y ago
There is an attempt for real-time transcription from the microphone at: https://whisper.ggerganov.com/stream/ It chunks the input in 5 second buffers and processes them independently. Results and performance are not gr
48.
by ggerganov 4y ago
I was recently playing with the GPT-2 and GPT-J models. Results are often non-sensical for any practical purposes, but I think can be used for making something fun - similar to your IRC bot idea. If you are interested in running these model
49.
by ggerganov 4y ago
About a month ago, I made a toy bot that listens to your voice with OpenAI Whisper, generates a response with GPT-2 and vocalizes the response using the Eleven Labs. The TTS quality produced by the Eleven Labs algorithm was mind-blowing to
50.
by ggerganov 4y ago
Here is a prototype of this that I hacked recently for iPhone: https://twitter.com/ggerganov/status/1605322535930941441
51.
by ggerganov 4y ago
Thanks for that - I have missed the block-sparse extension of the algorithm when I first read about it. And indeed this seems to be what the author means.
52.
by ggerganov 4y ago
> There has also been a wide variety of accuracy-degrading performance optimizations like Xformers and Flash Attention, which are great tools if you are open to trading accuracy for performance .. I wasn't aware that Flash Attention
53.
by ggerganov 4y ago
A follow up on this - I came up with an interesting strategy to achieve this. Still a prototype, but I think it looks very promising: https://github.com/ggerganov/whisper.cpp/pull/271 The source code is in th
54.
by ggerganov 4y ago
Hi, it's not obvious how to achieve this, but it feels it could be done. I think all the "tools" are available in the existing interface in `whisper.h` - for example, `whisper_get_probs()` gives you the probability for each t
55.
by ggerganov 4y ago
This is the smallest GPT-2 model so it usually generates gibberish. Maybe some better prompting could improve the results. Currently, the strategy is to simply prepend 8 lines of text (prompt/context) and keep appending every new trans
56.
by ggerganov 4y ago
Hey author here - I implemented `ggml` as a learning exercise. It allows me to easily port it to WebAssembly or iOS for example.
57.
by ggerganov 4y ago
Btw, there is the `yt-wsp.sh` helper script to download, convert and transcribe a video by given url: ./examples/yt-wsp.sh <video-url>
58.
by ggerganov 4y ago
Large v2 has already been added to `whisper.cpp` (check the pinned issues). I was thinking about adding a roadmap soon
59.
by ggerganov 4y ago
I have only implemented the Greedy decoder which is worse compared to the BeamSearch decoder in most cases.
60.
by ggerganov 4y ago
If you have a good GPU then you don't need `whisper.cpp`. Best use case currently is if you are running on Apple Silicon.

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