Instructions to use BlueNipples/Apocrypha-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use BlueNipples/Apocrypha-7b with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="BlueNipples/Apocrypha-7b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("BlueNipples/Apocrypha-7b")
model = AutoModelForCausalLM.from_pretrained("BlueNipples/Apocrypha-7b")

llama-cpp-python

How to use BlueNipples/Apocrypha-7b with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="BlueNipples/Apocrypha-7b",
	filename="GGUF/Apocrypha-7B-Q5_k.gguf",
)

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

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use BlueNipples/Apocrypha-7b with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf BlueNipples/Apocrypha-7b:IQ2_XXS_IMATRIX
# Run inference directly in the terminal:
llama-cli -hf BlueNipples/Apocrypha-7b:IQ2_XXS_IMATRIX

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf BlueNipples/Apocrypha-7b:IQ2_XXS_IMATRIX
# Run inference directly in the terminal:
llama-cli -hf BlueNipples/Apocrypha-7b:IQ2_XXS_IMATRIX

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 BlueNipples/Apocrypha-7b:IQ2_XXS_IMATRIX
# Run inference directly in the terminal:
./llama-cli -hf BlueNipples/Apocrypha-7b:IQ2_XXS_IMATRIX

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 BlueNipples/Apocrypha-7b:IQ2_XXS_IMATRIX
# Run inference directly in the terminal:
./build/bin/llama-cli -hf BlueNipples/Apocrypha-7b:IQ2_XXS_IMATRIX

Use Docker

docker model run hf.co/BlueNipples/Apocrypha-7b:IQ2_XXS_IMATRIX

LM Studio
Jan

vLLM

How to use BlueNipples/Apocrypha-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "BlueNipples/Apocrypha-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "BlueNipples/Apocrypha-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/BlueNipples/Apocrypha-7b:IQ2_XXS_IMATRIX

SGLang

How to use BlueNipples/Apocrypha-7b with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "BlueNipples/Apocrypha-7b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "BlueNipples/Apocrypha-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "BlueNipples/Apocrypha-7b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "BlueNipples/Apocrypha-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama

How to use BlueNipples/Apocrypha-7b with Ollama:

ollama run hf.co/BlueNipples/Apocrypha-7b:IQ2_XXS_IMATRIX

Unsloth Studio

How to use BlueNipples/Apocrypha-7b 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 BlueNipples/Apocrypha-7b 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 BlueNipples/Apocrypha-7b to start chatting

Using HuggingFace Spaces for Unsloth

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

Docker Model Runner
How to use BlueNipples/Apocrypha-7b with Docker Model Runner:
```
docker model run hf.co/BlueNipples/Apocrypha-7b:IQ2_XXS_IMATRIX
```

Lemonade

How to use BlueNipples/Apocrypha-7b with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull BlueNipples/Apocrypha-7b:IQ2_XXS_IMATRIX

Run and chat with the model

lemonade run user.Apocrypha-7b-IQ2_XXS_IMATRIX

List all available models

lemonade list

Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Design

The design intention is to create a pseudo-philosophical, pseudo-spiritual, pseudo counseling chatbob model for sounding ideas off. Like a mirror really. This obviously does not constitute medical advice, and if you are in need seek professional help. The name Apocrypha-7B comes from the fact that it's fake - this isn't a guide, friend or a guru. It's at best, if the model works, a sounding board. But I think such things might still be helpful for organising ones own thoughts. This model should still be able to role-play, but will likely play better as a 'helper' role of some sort given the counseling and theory of mind data if you do use it for role-play.

This mistral 7b model is a task arithmetic merge of Epiculous/Fett-uccine-7B (theory of mind and gnosis datasets), GRMenon/mental-mistral-7b-instruct-autotrain (mental health counseling conversations dataset), and teknium/Hermes-Trismegistus-Mistral-7B (open-hermes + occult datasets)

I will throw a GGUF or two inside a subfolder here.

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: ./Hermes-Trismegistus-7B
    parameters:
      weight: 0.35
  - model: ./mental-mistral-7b
    parameters:
      weight: 0.39
  - model: ./Fett-uccine-7B
    parameters:
      weight: 0.45
merge_method: task_arithmetic
base_model: ./Mistral-7B-v0.1
dtype: bfloat16

Resources used:

https://huggingface.co/teknium/Hermes-Trismegistus-Mistral-7B

https://huggingface.co/GRMenon/mental-mistral-7b-instruct-autotrain

https://huggingface.co/Epiculous/Fett-uccine-7B/tree/main

https://github.com/cg123/mergekit/tree/main

Downloads last month: 105

Safetensors

Model size

7B params

Tensor type

BF16

Model tree for BlueNipples/Apocrypha-7b

Quantizations

2 models