bliss
🧘 BLISS – a Benchmark for Language Induction from Small Sets (by taucompling)
llama-mistral
Inference code for Mistral and Mixtral hacked up into original Llama implementation (by dzhulgakov)
bliss | llama-mistral | |
---|---|---|
3 | 5 | |
9 | 373 | |
- | - | |
6.1 | 8.4 | |
9 months ago | 6 months ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
bliss
Posts with mentions or reviews of bliss.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-08.
- Password-protected language induction benchmark
-
Mistral 8x7B 32k model [magnet]
I wonder how it will rank on benchmarks which are password-protected to prevent test contamination, for example:
https://github.com/taucompling/bliss
- Bliss – A Benchmark for Language Induction from Small Sets
llama-mistral
Posts with mentions or reviews of llama-mistral.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-09.
- Inference code for Mistral and Mixtral hacked up
-
French AI startup Mistral secures €2B valuation
No. Without the inference code, the best we can have are guesses on its implementation, so the benchmark figures we can get could be quite wrong. It does seem better than Llama2-70B in my tests, which rely on the work done by Dmytro Dzhulgakov[0] and DiscoResearch[1].
But the point of releasing on bittorrent is to see the effervescence in hobbyist research and early attempts at MoE quantization, which are already ongoing[2]. They are benefitting from the community.
[0]: https://github.com/dzhulgakov/llama-mistral
[1]: https://huggingface.co/DiscoResearch/mixtral-7b-8expert
[2]: https://github.com/TimDettmers/bitsandbytes/tree/sparse_moe
- Code to run Mistral - mixtral-8x7b-32kseqlen
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New Mistral models just dropped (magnet links)
Someone made this. https://github.com/dzhulgakov/llama-mistral
-
Mistral 8x7B 32k model [magnet]
If anyone can help running this, would be appreciated. Resources so far:
- https://github.com/dzhulgakov/llama-mistral
What are some alternatives?
When comparing bliss and llama-mistral you can also consider the following projects:
megablocks-public
llama.cpp - LLM inference in C/C++