ai_story_scale
StableLM
ai_story_scale | StableLM | |
---|---|---|
2 | 43 | |
9 | 15,832 | |
- | 0.1% | |
3.6 | 5.0 | |
9 months ago | 12 months ago | |
Jupyter Notebook | Jupyter Notebook | |
Creative Commons Attribution Share Alike 4.0 | Apache License 2.0 |
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.
ai_story_scale
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Survey Results Preview (90% Progress Milestone): Morpho
To get a better idea of what is going on with Morpho stories, here are two typical outputs from the Morpho preset.
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Survey Results Preview III (75% Progress): Basic Coherence
Two typical outputs are here.
StableLM
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The Era of 1-bit LLMs: ternary parameters for cost-effective computing
https://github.com/Stability-AI/StableLM?tab=readme-ov-file#...
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Stable LM 3B: Bringing Sustainable, High-Performance LMs to Smart Devices
https://mistral.ai/news/announcing-mistral-7b/
looking at the 3b results (here https://github.com/Stability-AI/StableLM#stablelm-alpha-v2 ?), it looks like Mistral (which outperforms Llama-2 13b) is far more powerful
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FreeWilly 1 and 2, two new open-access LLMs
Does this mean Stability gave up on StableLM?
I notice that the repo hasn’t been updated since April, and a question asking for an update has been ignored for at least a month: https://github.com/Stability-AI/StableLM/issues/83
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In five years, there will be no programmers left, believes Stability AI CEO
I'm not "ignoring" StableLM, if anything it's the impetus for my post. The alpha models were so bad and unusable that it seems they may have simply abandoned the project. It's clear they basically didn't know what they were doing, which is silly for a company of their size and specialization.
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Losing the plot
1) StableLM released a checkpoint at 800B for their 3B and 7B at 800B tokens with 4096 context size, but perform very poorly on different benchmarks and finetuning is discouraged with such a weak base model
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UAE's Technology Innovation Institute Launches Open-Source "Falcon 40B" Large Language Model for Research & Commercial Utilization
It is the best open-source model currently available. Falcon-40B outperforms LLaMA, StableLM, RedPajama, MPT, etc. See the OpenLLM Leaderboard.
- Consulta API GPT
- Google "We Have No Moat, And Neither Does OpenAI"
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New to StableLM--is it possible to use this locally to fine-tune on a small subset of documents yet?
Someone shared this link on another recent post
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[N] Stability AI releases StableVicuna: the world's first open source chatbot trained via RLHF
Github: https://github.com/Stability-AI/StableLM
What are some alternatives?
augmented-interpretable-models - Interpretable and efficient predictors using pre-trained language models. Scikit-learn compatible.
lm-evaluation-harness - A framework for few-shot evaluation of language models.
Smarty-GPT - A wrapper of LLMs that biases its behaviour using prompts and contexts in a transparent manner to the end-users
llama.cpp - LLM inference in C/C++
reweight-gpt - Reweight GPT - a simple neural network using transformer architecture for next character prediction
alpaca_lora_4bit