Dev tools · alternatives · 2026

24 alternatives to I Created ErisForge, a Python Library for Abliteration of LLMs

ErisForge is a Python library designed to modify Large Language Models (LLMs) by applying transformations to their internal layers. Named after Eris, the goddess of strife and discord, ErisForge allows you to alter model behavior in a controlled manner, creating both ablated and augmented versions of LLMs that respond differently to specific types of input. It is also quite useful to perform studies on propaganda and bias in LLMs (planning to experiment with deepseek). Features - Modify internal layers of LLMs to produce altered behaviors. - Ablate or enhance model responses with the…

ErisForge is a Python library that modifies Large Language Models by transforming their internal layers to alter model behavior in controlled ways. It enables researchers and developers to create ablated or augmented… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

1
ChainForge, a visual tool for prompt engineering and LLM evaluation▲177
Hi HN! We’re been working hard on this low-code tool for rapid prompt discovery, robustness testing and LLM evaluation. We’ve just released documentation to help new users learn how to use it and what it can already do. Let us know what you think! :)
2023 · chainforge.ai · its alternatives →
2
I built a tiny LLM to demystify how language models work▲915
Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.
Apr 2026 · github.com · its alternatives →
3
Wordllama – Things you can do with the token embeddings of an LLM▲370
After working with LLMs for long enough, I found myself wanting a lightweight utility for doing various small tasks to prepare inputs, locate information and create evaluators. This library is two things: a very simple model and utilities that inference it (eg. fuzzy deduplication). The target platform is CPU, and it’s intended to be light, fast and pip installable — a library that lowers the barrier to working with strings semantically. You don’t need to install pytorch to use it, or any deep learning runtimes. How can this be accomplished? The model is simply token embeddings that are…
2024 · github.com · its alternatives →
4
TensorZero▲307
Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
2025 · github.com · its alternatives →
5
We've open-sourced our LLM attention visualization library▲197
Inspectus allows you to create interactive visualizations of attention matrices with just a few lines of Python code. It’s designed to run smoothly in Jupyter notebooks through an easy-to-use Python API. Inspectus provides multiple views to help you understand language model behaviors. If you have any questions, feel free to ask!
2024 · github.com · its alternatives →
6
LLM Explorer▲152
Find your best LLM for a local inference
2023 · its alternatives →
7
ThoughtDAG – An editable context graph for LLM conversations▲136
ThoughtDAG indexes local agent conversations across tools, finds the turns relevant to your work, and turns them into editable context graphs.
Aug 2026 · chenxiachan.github.io · its alternatives →
8
Twigg▲157
Hi HN, we’re Jamie and Matti, co-founders of Twigg. During our master’s we continually found the same pain points cropping up when using LLMs. The linear nature of typical LLMs interfaces - like ChatGPT and Claude - made it really easy to get lost without any easy way to visualise or navigate your project. Worst of all, none of them are well suited for long term projects. We found ourselves spending days using the same chat, only for it to eventually break. Transferring context from one chat to another is also cumbersome. We decided to build something more intuitive to the ways humans think.…
2025 · twigg.ai · its alternatives →
9
LLM, a Rust Crate/CLI for CPU Inference of LLMs (LLaMA, GPT-NeoX, etc.)▲45
G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…
2023 · github.com · its alternatives →
10
I built a web tool to see and edit what an AI thinks before it answers▲34
I run a small AI lab and playground and got super excited about Anthropics paper "Verbalizable Representations Form a Global Workspace in Language Models" (https://transformer-circuits.pub/2026/workspace/index.html) It talks about how they use a tool they call a Jacobian Lens to view inside the middle layers of LLM while it's working before it commits to a word (token). I wanted to see if I could get a version of this running on the open models and to my surprise it worked! I ran some experiments with it and build a public facing free tool anyone can use with your…
Jul 2026 · lucid.earthpilot.ai · its alternatives →
11
Using LLMs and Embeddings to classify application errors▲65
Hi Hacker News! We’re Vadim and Chris from Highlight.io [1]. We do web app monitoring and are working on using LLMs/embeddings to add new functionality to our error monitoring product. Given that there’s a lot of founders/engineers using LLMs in their products, we figured we’d share how we built the new functionality, their impact on our workflows, and how you can try it out. Our goal was to build two features: (1) tagging errors (e.g. deeming an error as “authentication error” or a “database error”); and (2) grouping similar errors together (e.g. two errors that have a different…
2023 · github.com · its alternatives →
12
LLMs can be susceptible to a new kind of malware▲17
New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.
2023 · github.com · its alternatives →
13
Improve Text-to-SQL Accuracy with LLM▲17
A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL - eosphoros-ai/DB-GPT-Hub
2023 · github.com · its alternatives →
14
Bash4LLM+ – A lightweight, dependency-free Bash wrapper for LLM APIs▲60
Bash4LLM is a single-file Bash wrapper for interacting with LLMs from the terminal. I created it because I wanted something simple that worked without installing Python, Node, or any other runtime. It uses only Bash, curl, and jq. You can send prompts, start a small chat, process files line by line, stream output, and save session metadata in JSON format. I tried to make it safe and predictable: no use of the system /tmp, no use of eval. Groq is supported by default, and other providers can be added with dedicated Bash scripts in the extras/providers/ folder. Example: echo…
Jun 2026 · github.com · its alternatives →
15
Spanda – Sub-microsecond LLM epistemic uncertainty in Rust▲13
Zero-cost epistemic uncertainty quantification & hallucination detection for LLMs (90,000x faster than Semantic Entropy) - Adarshent/Spnda
Sep 2026 · github.com · its alternatives →
16
Toolkit for LLM Fine-Tuning, Ablating and Testing▲14
Hello all! Very happy to share this toolkit that allows you to fine-tune your choice of open-source LLMs on your data! The toolkit also allows you to run ablation studies across LLMs, prompt designs, training configurations, and can ingest different data files -- all through just ONE YAML file! After fine-tuning, you can also run a bunch of tests to ensure that the fine-tuned LLM behaves as expected, enabling faster time-to-production! Why this toolkit? Why now? While closed-source LLMs have become popular for chat-based applications, enterprises are considering a shift to self-hosted SLMs…
2024 · github.com · its alternatives →
17
Extrai – An open-source tool to fight LLM randomness in data extraction▲5
A few months ago I was working on a flight search engine that would include pet transport costs (I know a few by hearth but storing them and make the calculations in the UI would be nice) While I was collecting pet pricing from several airlines I strugled to extract data in a common format without hallucinated values. That's when I thought: What if I use multiple LLMs and take the most common response to improve accuracy? This idea became this new project. You provide your documents, an SQLModel schema, an LLM provider, plus what you'd like to extract and Extrai does the rest. Including…
Nov 2025 · github.com · its alternatives →
18
Create LLM graders and run evals in JavaScript with one file▲28
Hi HN! Run it: OPENROUTER_API_KEY="sk" npx bff-eval --demo We built a tool to help people take LLM outputs and easily grade them / eval them to know how good an assistant response is. We've built a number of LLM apps, and while we could ship decent tech demos, we were disappointed with how they'd perform over time. We worked with a few companies who had the same problem, and found out scientifically building prompts and evals is far from a solved problem... writing these things feels more like directing a play than coding. Inspired by Anthropic's constitutional ai concepts, and amazing…
2025 · github.com · its alternatives →
19
LLM-docs, software documentation intended for consumption by LLMs▲28
I was inspired by a recent tweet by Andrej Karpathy, as well as my own experience copying and pasting a bunch of html docs into Claude yesterday and bemoaning how long-winded and poorly formatted it was. I’m trying to decide if I should make it into a full-fledged service and completely automate the process of generating the distilled documentation. Problem is that it would cost a lot in API tokens and wouldn’t generate any revenue (plus it would have to be updated as documentation changes significantly). Maybe Anthropic wants to fund it as a public good? Let me know!
2025 · github.com · its alternatives →
20
I implemented evals metrics for LLMs that runs locally on your machine▲22
The LLM Evaluation Framework. Contribute to confident-ai/deepeval development by creating an account on GitHub.
2023 · github.com · its alternatives →
21
LoongForge-A high-performance training framework for LLM, VLM, VLA, Wan▲10
A high-performance framework for training LLMs, VLMs, diffusion, and embodied models on NVIDIA GPUs and Kunlun XPUs. - GitHub - baidu-baige/LoongForge: A high-performance framework for training LLMs, VLMs, diffusion, and embodied models on NVIDIA GPUs and Kunlun XPUs.
May 2026 · github.com · its alternatives →
22
Your AI Slop Bores Me▲17
When the LLM so ahh you lowk take over its job
Mar 2026 · youraislopbores.me · its alternatives →
23
LLM Thought Visualization▲24
To know what models don't say out loud. Contribute to ninjahawk/Subtext development by creating an account on GitHub.
Jul 2026 · github.com · its alternatives →
24
UpTrain – A Practical Approach to Finetuning LLMs for Custom Use-Cases▲10
2023 · github.com · its alternatives →

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