Instructions to use DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF", dtype="auto")

llama-cpp-python

How to use DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF",
	filename="sunk_cost_fallacy-8b-model_stock.q6_k.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K
# Run inference directly in the terminal:
llama-cli -hf DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K
# Run inference directly in the terminal:
llama-cli -hf DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K

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 DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K
# Run inference directly in the terminal:
./llama-cli -hf DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K

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 DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K

Use Docker

docker model run hf.co/DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K

LM Studio
Jan
Ollama
How to use DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF with Ollama:
```
ollama run hf.co/DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K
```

Unsloth Studio new

How to use DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-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 DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-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 DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF to start chatting

Pi new

How to use DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K

Run Hermes

hermes

Docker Model Runner
How to use DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF with Docker Model Runner:
```
docker model run hf.co/DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K
```

Lemonade

How to use DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull DreadPoor/Sunk_Cost_Fallacy-8B-Model_Stock-GGUF:Q6_K

Run and chat with the model

lemonade run user.Sunk_Cost_Fallacy-8B-Model_Stock-GGUF-Q6_K

List all available models

lemonade list

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the Model Stock merge method using SentientAGI/Dobby-Mini-Unhinged-Llama-3.1-8B as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: DreadPoor/Rusted_Gold-8B-LINEAR+kromcomp/L3-Umbral-Mind-r128-LoRA
  - model: DreadPoor/ichor_1.1-8B-Model_Stock
  - model: DreadPoor/Aspire-8B-model_stock
  - model: Yuma42/Llama3.1-IgneousIguana-8B
merge_method: model_stock
base_model: SentientAGI/Dobby-Mini-Unhinged-Llama-3.1-8B
normalize: false
int8_mask: true
dtype: bfloat16