Instructions to use LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF with Ollama:
ollama run hf.co/LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF with Docker Model Runner:
docker model run hf.co/LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF:Q4_K_M
- Lemonade
How to use LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull LoneStriker/OpenHermes-2.5-Code-290k-13B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.OpenHermes-2.5-Code-290k-13B-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
OpenHermes-2.5-Code-290k-13B
OpenHermes-2.5-Code-290k-13B is a state of the art Llama-2 Fine-tune, which is trained on additional code dataset. This model is trained on my existing dataset OpenHermes-2.5-Code-290k. This dataset is amalgamation of two datasets. I have used OpenHermes-2.5 a super quality dataset made avaliable by teknium. Other datset is my own Code-290k-ShareGPT. Dataset is in Vicuna/ShareGPT format. There are around 1.29 million set of conversations. I have cleaned the dataset provided by Teknium and removed metadata such as "source" & "category" etc. This dataset has primarily synthetically generated instruction and chat samples.
This model has enhanced coding capabilities besides other capabilities such as Blogging, story generation, Q&A and many more.
Training:
Entire model was trained on 4 x A100 80GB. For 2 epoch, training took 21 Days. Fschat & DeepSpeed codebase was used for training purpose. This was trained on Llama-2 by Meta.
This is a full fine tuned model. Links for quantized models will be updated soon.
GPTQ, GGUF, AWQ & Exllama
GPTQ: TBA
GGUF: TBA
AWQ: TBA
Exllama v2: TBA
Example Prompt:
This is a conversation with your helpful AI assistant. AI assistant can generate Code in various Programming Languages along with necessary explanation. It can generate Story, Blogs .....
Context
You are a helpful AI assistant.
USER: <prompt>
ASSISTANT:
You can modify above Prompt as per your requirement. I have used ShareGPT/Vicuna format v1.1 .
I want to say special Thanks to the Open Source community for helping & guiding me to better understand the AI/Model development.
Thank you for your love & support.
Example Output
I will update soon.
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