- Libraries
- Keras
How to use Tensormorph/distillgpt2 with Keras:
# !pip install -U keras tensorflow huggingface_hub
# Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here;
# "jax" and "torch" also work for computation once TensorFlow is installed.
import os
os.environ["KERAS_BACKEND"] = "tensorflow"
import keras
model = keras.saving.load_model("hf://Tensormorph/distillgpt2")
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Tensormorph/distillgpt2 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 Tensormorph/distillgpt2:F16
# Run inference directly in the terminal:
llama cli -hf Tensormorph/distillgpt2:F16
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Tensormorph/distillgpt2:F16
# Run inference directly in the terminal:
llama cli -hf Tensormorph/distillgpt2:F16
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 Tensormorph/distillgpt2:F16
# Run inference directly in the terminal:
./build/bin/llama cli -hf Tensormorph/distillgpt2:F16
Use Docker
docker model run hf.co/Tensormorph/distillgpt2:F16
- Llama new
- LM Studio
- Jan
- Ollama
How to use Tensormorph/distillgpt2 with Ollama:
ollama run hf.co/Tensormorph/distillgpt2:F16
- Unsloth Desktop
- Docker Model Runner
How to use Tensormorph/distillgpt2 with Docker Model Runner:
docker model run hf.co/Tensormorph/distillgpt2:F16
- Lemonade
How to use Tensormorph/distillgpt2 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/
lemonade pull Tensormorph/distillgpt2:F16
Run and chat with the model
lemonade run user.distillgpt2-F16
List all available models
lemonade list
- Atomic Chat
