Nicolay Gerold
@nicolaygerold
Nicolay Gerold
https://github.com/huggingface/chat-ui - Amazing clean UI with very good web search, my go to currently. (they added the ability to do it all locally very recently!)
https://github.com/oobabooga/text-generation-webui - Best overall, supports any model format and has many extensions
https://github.com/ParisNeo/lollms-webui/ - Has PDF, stable diffusion... See more
https://github.com/oobabooga/text-generation-webui - Best overall, supports any model format and has many extensions
https://github.com/ParisNeo/lollms-webui/ - Has PDF, stable diffusion... See more
r/LocalLLaMA - Reddit
First time here? Go to our setup guide
Features
Features
- 🤖 Multiple model integrations: OpenAI, transformers, llama.cpp, exllama2, mamba
- 🖍️ Simple and powerful prompting primitives based on the Jinja templating engine
- 🚄 Multiple choices, type constraints and dynamic stopping
- ⚡ Fast regex-structured generation
- 🔥 Fast JSON generation following a JSON schema
outlines-dev • GitHub - outlines-dev/outlines: Neuro Symbolic Text Generation
DiscoLM German 7B v1 - GGUF
Model creator: Disco Research
Original model: DiscoLM German 7B v1
Description
This repo contains GGUF format model files for Disco Research's DiscoLM German 7B v1.
These files were quantised using hardware kindly provided by Massed Compute.
About GGUF
GGUF is a new format introduced by the llama.cpp team on August 21st 2023.... See more
Model creator: Disco Research
Original model: DiscoLM German 7B v1
Description
This repo contains GGUF format model files for Disco Research's DiscoLM German 7B v1.
These files were quantised using hardware kindly provided by Massed Compute.
About GGUF
GGUF is a new format introduced by the llama.cpp team on August 21st 2023.... See more
TheBloke/DiscoLM_German_7b_v1-GGUF · Hugging Face
Flow isn’t a state of learning it is a state of expression for already learned skills.
Andrew Huberman • Using Failures, Movement & Balance to Learn Faster
Most problems occur that people cannot regulate the stress (levels of cortisol and epinephrine in the brain) to stay calm and select the right action.
Andrew Huberman • Using Cortisol & Adrenaline to Boost Our Energy & Immune System
End to end ML Project
Project setup:
Model training:
Run: python main.py
Model... See more
Project setup:
- Open this in VSCode
- Install Dev Containers
- Do Cmd + Shift + P -> Dev Containers: Rebuild Container Without Cache
- Activate the conda virtual environment: source activate endtoend
- Inside Dev Container, run mlflow and prefect local servers: nohup bash ./start_backend.sh
Model training:
Run: python main.py
Model... See more
arghhjayy • GitHub - arghhjayy/EndToEndML: End to end ML pipeline written with open source tools exclusively
The way that most RLHF is done to date has the entire response from a language model get an associated score. To anyone with an RL background, this is disappointing, because it limits the ability for RL methods to make connections about the value of each sub-component of text. Futures have been pointed to where this multi-step optimization comes at... See more
Nathan Lambert • The Q* hypothesis: Tree-of-thoughts reasoning, process reward models, and supercharging synthetic data
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
Fireworks Console
TL;DR
LLMLingua utilizes a compact, well-trained language model (e.g., GPT2-small, LLaMA-7B) to identify and remove non-essential tokens in prompts. This approach enables efficient inference with large language models (LLMs), achieving up to 20x compression with minimal performance loss.
... See more
LLMLingua utilizes a compact, well-trained language model (e.g., GPT2-small, LLaMA-7B) to identify and remove non-essential tokens in prompts. This approach enables efficient inference with large language models (LLMs), achieving up to 20x compression with minimal performance loss.
... See more