Instructions to use Geweron/GPT2-Chat-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 Geweron/GPT2-Chat-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 Geweron/GPT2-Chat-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf Geweron/GPT2-Chat-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Geweron/GPT2-Chat-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf Geweron/GPT2-Chat-GGUF:Q8_0
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 Geweron/GPT2-Chat-GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf Geweron/GPT2-Chat-GGUF:Q8_0
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 Geweron/GPT2-Chat-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Geweron/GPT2-Chat-GGUF:Q8_0
Use Docker
docker model run hf.co/Geweron/GPT2-Chat-GGUF:Q8_0
- LM Studio
- Jan
- Ollama
How to use Geweron/GPT2-Chat-GGUF with Ollama:
ollama run hf.co/Geweron/GPT2-Chat-GGUF:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use Geweron/GPT2-Chat-GGUF with Docker Model Runner:
docker model run hf.co/Geweron/GPT2-Chat-GGUF:Q8_0
- Lemonade
How to use Geweron/GPT2-Chat-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Geweron/GPT2-Chat-GGUF:Q8_0
Run and chat with the model
lemonade run user.GPT2-Chat-GGUF-Q8_0
List all available models
lemonade list
- Atomic Chat
GPT-2 for Dialogue
This repository contains gpt2 (the standard 124M parameter version) fine-tuned for improved conversational performance. The model was trained on a diverse, custom dataset of English dialogues.
Original model https://huggingface.co/openai-community/gpt2
Project Goal: The primary objective is to push the capabilities of the small GPT-2 architecture for conversational tasks, including general chat and question answering. The focus is on creating a capable yet lightweight dialogue model. This model represents an initial stage, with further training planned.
Training Data: A custom corpus of English dialogues spanning multiple general topics was used for fine-tuning.
Potential Use Cases:
- Casual conversation partner
- Base for further fine-tuning on specific dialogue tasks
- Research into efficient conversational models
Disclaimer:
This model is a work in progress. As it's based on gpt2, it may not perform as well as larger models and may exhibit limitations common to language models of this size.
- Downloads last month
- 16
8-bit