Instructions to use CorticalStack/mistral-7b-openhermes-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use CorticalStack/mistral-7b-openhermes-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="CorticalStack/mistral-7b-openhermes-gguf",
	filename="mistral-7b-openhermes.Q4_K_M.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use CorticalStack/mistral-7b-openhermes-gguf with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf CorticalStack/mistral-7b-openhermes-gguf:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf CorticalStack/mistral-7b-openhermes-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf CorticalStack/mistral-7b-openhermes-gguf:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf CorticalStack/mistral-7b-openhermes-gguf:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf CorticalStack/mistral-7b-openhermes-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf CorticalStack/mistral-7b-openhermes-gguf:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf CorticalStack/mistral-7b-openhermes-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf CorticalStack/mistral-7b-openhermes-gguf:Q4_K_M

Use Docker

docker model run hf.co/CorticalStack/mistral-7b-openhermes-gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use CorticalStack/mistral-7b-openhermes-gguf with Ollama:
```
ollama run hf.co/CorticalStack/mistral-7b-openhermes-gguf:Q4_K_M
```

Unsloth Studio

How to use CorticalStack/mistral-7b-openhermes-gguf with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for CorticalStack/mistral-7b-openhermes-gguf to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for CorticalStack/mistral-7b-openhermes-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for CorticalStack/mistral-7b-openhermes-gguf to start chatting

Docker Model Runner
How to use CorticalStack/mistral-7b-openhermes-gguf with Docker Model Runner:
```
docker model run hf.co/CorticalStack/mistral-7b-openhermes-gguf:Q4_K_M
```

Lemonade

How to use CorticalStack/mistral-7b-openhermes-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull CorticalStack/mistral-7b-openhermes-gguf:Q4_K_M

Run and chat with the model

lemonade run user.mistral-7b-openhermes-gguf-Q4_K_M

List all available models

lemonade list

CorticalStack commited on Feb 17, 2024

Commit

01e7913

verified ·

1 Parent(s): 335a6c8

Upload folder using huggingface_hub

Browse files

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+---
+license: apache-2.0
+---
+# CorticalStack/mistral-7b-openhermes
+A collection of GGUF quantised versions of [CorticalStack/mistral-7b-openhermes-sft](https://huggingface.co/CorticalStack/mistral-7b-openhermes-sft).
+The main branch model is quantised using GGUF format Q4_K_M.
+GGUF is a format that replaces GGML, which is no longer supported by llama.cpp.
+An incomplete list of clients and libraries that are known to support GGUF:
+* [llama.cpp](https://github.com/ggerganov/llama.cpp). The source project for GGUF. Offers a CLI and a server option.
+* [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
+* [KoboldCpp](https://github.com/LostRuins/koboldcpp), a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
+* [GPT4All](https://gpt4all.io/index.html), a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel.
+* [LM Studio](https://lmstudio.ai/), an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration. Linux available, in beta as of 27/11/2023.
+* [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui), a great web UI with many interesting and unique features, including a full model library for easy model selection.
+* [Faraday.dev](https://faraday.dev/), an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration.
+* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
+* [candle](https://github.com/huggingface/candle), a Rust ML framework with a focus on performance, including GPU support, and ease of use.
+* [ctransformers](https://github.com/marella/ctransformers), a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server.

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