Instructions to use tosin/dialogpt_afriwoz_pidgin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tosin/dialogpt_afriwoz_pidgin with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tosin/dialogpt_afriwoz_pidgin")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("tosin/dialogpt_afriwoz_pidgin") model = AutoModelForCausalLM.from_pretrained("tosin/dialogpt_afriwoz_pidgin", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use tosin/dialogpt_afriwoz_pidgin with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tosin/dialogpt_afriwoz_pidgin" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tosin/dialogpt_afriwoz_pidgin", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/tosin/dialogpt_afriwoz_pidgin
- SGLang
How to use tosin/dialogpt_afriwoz_pidgin 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 "tosin/dialogpt_afriwoz_pidgin" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tosin/dialogpt_afriwoz_pidgin", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "tosin/dialogpt_afriwoz_pidgin" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tosin/dialogpt_afriwoz_pidgin", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use tosin/dialogpt_afriwoz_pidgin with Docker Model Runner:
docker model run hf.co/tosin/dialogpt_afriwoz_pidgin
Download pytorch_model.bin from tosin/dialogpt_afriwoz_pidgin: direct link, hf CLI and curl.
- Browser
- Download file 510 MB
-
https://huggingface.co/tosin/dialogpt_afriwoz_pidgin/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://tosin/dialogpt_afriwoz_pidgin@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tosin/dialogpt_afriwoz_pidgin/resolve/refs%2Fpr%2F1/pytorch_model.bin
510 MB
- Xet hash:
- 7255f5636c2de3ffb1f33333e5de6bde11a952c5f3f18e87d7dad7d8d20258b3
- Size of remote file:
- 510 MB
- SHA256:
- d9f49074ae7feb99bc5c1599b588943282b0b533b6abacc66669fa52ecd27e1e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.