paulcjh

8 ms·

61.
Adobe introduces generative artificial intelligence for music creation(itc.ua)
3 points by paulcjh 3y ago|0 comments
62.
Artificial intelligence deepfakes: The threat is profound and real(berkshireeagle.com)
1 points by paulcjh 3y ago|0 comments
63.
by paulcjh 3y ago
There's not really a trade off, just less VRAM.
64.
Show HN: Fractional GPUs for AI(docs.mystic.ai)
8 points by paulcjh 3y ago|2 comments
65.
Is Google's Gemini chatbot woke by accident, or by design?(economist.com)
7 points by paulcjh 3y ago|2 comments
66.
Gaganyaan: India names astronauts for maiden space flight(bbc.co.uk)
2 points by paulcjh 3y ago|0 comments
67.
by paulcjh 3y ago
The cost of their chips need to some down first, way too big and expensive
68.
Call-Center Firm Sinks on Klarna Claims AI Is Doing Agents' Jobs(bloomberg.com)
18 points by paulcjh 3y ago|2 comments
69.
Amazon denies AI was used to recreate original actors' voices as lawsuit filed(independent.co.uk)
3 points by paulcjh 3y ago|0 comments
70.
by paulcjh 3y ago
Really cool!
71.
Gemma 7B Deployment on A100s(mystic.ai)
2 points by paulcjh 3y ago|0 comments
72.
by paulcjh 3y ago
Managed to get 1.8k tokens per second with a batch of 60 when running vLLM with Mistral 7B on an A100 40GB in bfloat16 mode. Pretty damn fast! vllm==0.2.0 got released an hour or so ago, so it's pretty fresh. Let me know fi you'd
73.
VLLM with Mistral 7B guide and benchmarks (1.8k+ tokens/s)(docs.mystic.ai)
3 points by paulcjh 3y ago|3 comments
74.
by paulcjh 3y ago
Amen to that!
75.
by paulcjh 3y ago
Their new 7B model beats the Llama 2 7B in all benchmarks that they provided, and in many cases the 13B variation. This is a basic demo for you to try it it, seeing the best results with the instruct variation, and JSON extraction seems goo
76.
Mistral AI 7B – beats Llama 2 7B and 13B(mystic.ai)
3 points by paulcjh 3y ago|3 comments
77.
OpenJourney XL – Finetuned SDXL on Midjourney v5 Dataset(mystic.ai)
2 points by paulcjh 3y ago|0 comments
78.
by paulcjh 3y ago
Hope that you enjoy the guide, below is also some cost/speed comparisons for running the models with vLLM: - 7B, 1x A100, 25GB VRAM, 49 tok/s, $0.0113 /1k tok - 13B, 1x A100, 37GB VRAM, 32 tok/s, $0.0174 /1k tok - 7
79.
Llama 2 chat with vLLM and tensor parallel guide(docs.mystic.ai)
1 points by paulcjh 3y ago|1 comments
80.
SDXL discord bot (running on 1.3k servers)(discord.com)
2 points by paulcjh 3y ago|0 comments
81.
GPU sharing with multiple Python environments white paper(mystic.ai)
10 points by paulcjh 3y ago|0 comments
82.
by paulcjh 3y ago
In the context of building a product it’s normally best to do some of that final 10% as early as possible. Fail fast, see what works fast. I’ve had so many projects not get to 100% due to things I could have validated in the first 5%
83.
by paulcjh 3y ago
Any performance benchmarks compared to other LLMs? Also, any performance increases on the orig Falcon model in inference speed? We ditched most of our focus on Falcon 40B after Llama 2 70B came out, both the tokens per sec and quality of re
84.
by paulcjh 3y ago
I know people are working on it - but IMO it's not spoken about anywhere near as much as slapping more GPUs on a problem. I'm on about enterprise workload orchestration not just making a model faster
85.
by paulcjh 3y ago
Activating type checking mode in VSCode was a game changer for me when running python, help catch loads of the edge cases for correctly for some production code
86.
by paulcjh 3y ago
By far the biggest issue it utilisation of the GPUs, if people worked on that instead of throwing more power at problems this would be way less of a problem