Instructions to use Tensormorph/distillgpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- 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
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 Tensormorph/distillgpt2:F16 # Run inference directly in the terminal: ./llama-cli -hf Tensormorph/distillgpt2:F16
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 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
- 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
Download tinygpt/tensorflow/tiny.float16.tflite from Tensormorph/distillgpt2: direct link, hf CLI and curl.
- Browser
- Download file 291 kB
-
https://huggingface.co/Tensormorph/distillgpt2/resolve/main/tinygpt/tensorflow/tiny.float16.tflite
- Command line
-
hf download hf://Tensormorph/distillgpt2/tinygpt/tensorflow/tiny.float16.tflite
-
curl -L -o tiny.float16.tflite https://huggingface.co/Tensormorph/distillgpt2/resolve/main/tinygpt/tensorflow/tiny.float16.tflite
291 kB
- Xet hash:
- cb224d03d87ff4140f3521882aec3c055a0855bc233abb7626b071e7f235aecf
- Size of remote file:
- 291 kB
- SHA256:
- 4b4627622b818bfbb84ce835ed50d406727bcd84390b08ea61c8d97fe13bbd00
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