Nicolay Gerold
@nicolaygerold
Nicolay Gerold
Don't just randomly draw boxes and arrows. There are some important, well-defined diagrams that are extremely useful for software dev:
→ Sequence diagrams
→ Architecture diagrams
→ Entity-relationship diagrams
→ State machine diagrams
→ Component diagrams (dependencies)
→ Sequence diagrams
→ Architecture diagrams
→ Entity-relationship diagrams
→ State machine diagrams
→ Component diagrams (dependencies)
David K @DavidKPiano
filesystem_spec
A specification for pythonic filesystems.
Install
pip install fsspec
would install the base fsspec. Various optionally supported features might require specification of custom extra require, e.g. pip install fsspec[ssh] will install dependencies for ssh backends support. Use pip install fsspec[full] for installation of all known... See more
A specification for pythonic filesystems.
Install
pip install fsspec
would install the base fsspec. Various optionally supported features might require specification of custom extra require, e.g. pip install fsspec[ssh] will install dependencies for ssh backends support. Use pip install fsspec[full] for installation of all known... See more
fsspec • GitHub - fsspec/filesystem_spec: A specification that python filesystems should adhere to.
Three levels of product work: you have to talk with the people at their level and with the corresponding language. 1. Impact: level of C-level2. Execution: level of the PMs3. Optics
lennysnewsletter.com • Shreyas Doshi on Pre-Mortems, the LNO Framework, the Three Levels of Product Work, Why Most Execution Problems Are Strategy Problems, and ROI vs. Opportunity Cost Thinking
pair-preference-model-LLaMA3-8B by RLHFlow: Really strong reward model, trained to take in two inputs at once, which is the top open reward model on RewardBench (beating one of Cohere’s).
DeepSeek-V2 by deepseek-ai (21B active, 236B total param.): Another strong MoE base model from the DeepSeek team. Some people are questioning the very high MMLU... See more
DeepSeek-V2 by deepseek-ai (21B active, 236B total param.): Another strong MoE base model from the DeepSeek team. Some people are questioning the very high MMLU... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
We can detect factually inconsistent summaries via the natural language inference (NLI) task. The NLI task works like this: Given a premise sentence and a hypothesis sentence, the goal is to predict if the hypothesis is entailed by, neutral, or contradicts the premise.
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
Take a look at our official page for user documentation and examples: langtest.org
Key Features
Key Features
- Generate and execute more than 50 distinct types of tests only with 1 line of code
- Test all aspects of model quality: robustness, bias, representation, fairness and accuracy.
- Automatically augment training data based on test results (for select models)
- Sup
GitHub - BrunoScaglione/langtest: Deliver safe & effective language models
LLMs and LLM Evaluation
![Thumbnail of Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]](https://d1l054mla94ehg.cloudfront.net/media/images/thumbnails/curation/b60c2084b727406da207347fcb136726/thumbnail.png?height=75&dpr=2)
Here’s his 5-step process:
1/ Question every requirement
Never except that a requirement came from a department, such as from “the legal department” or “the safety department”. Requirements from smart people are dangerous because people are less likely to question them.
2/ Delete any part or process you can
You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough.
3/ Simplify and optimize
This should come AFTER step two.
4/ Accelerate cycle time
Every process can be speeded up. But only do this AFTER you have followed the first three steps.
5/ Automate
That comes last. Wait until all requirements have been questioned, parts and processes deleted, and the bugs were shaken out.
There were also additional “rules” to the Algorithm including:
1/ Camaraderie is dangerous. It makes it hard for people to challenge each other’s work.
2/ All technical managers must have hands-on experience. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword.
3/ The only rules are the ones dictated by the laws of physics. Everything else is a recommendation.
Lightning-fast OSS ModelsTry our APIExperience the world's fastest LLM inference platform. Use a state-of-the-art, open-source model or fine-tune and deploy your own at no additional cost, with Fireworks.ai.Query Large Language Models with Fireworks.aiIt is super easy to get started with Fireworks.ai LLM API. You can use the Python client (install... See more