Instructions to use kplro/model_proga with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kplro/model_proga with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="kplro/model_proga")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("kplro/model_proga") model = AutoModelForCausalLM.from_pretrained("kplro/model_proga", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use kplro/model_proga with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "kplro/model_proga" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kplro/model_proga", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/kplro/model_proga
- SGLang
How to use kplro/model_proga 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 "kplro/model_proga" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kplro/model_proga", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "kplro/model_proga" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kplro/model_proga", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use kplro/model_proga with Docker Model Runner:
docker model run hf.co/kplro/model_proga
Download model.pt from kplro/model_proga: direct link, hf CLI and curl.
- Browser
- Download file 3.14 GB
-
https://huggingface.co/kplro/model_proga/resolve/main/model.pt
- Command line
-
hf download hf://kplro/model_proga/model.pt
-
curl -L -o model.pt https://huggingface.co/kplro/model_proga/resolve/main/model.pt
3.14 GB
- Xet hash:
- fb9963383a5dba4ad544d73696f8fd794b3c225fecd41b4b12e0c096920d2c5a
- Size of remote file:
- 3.14 GB
- SHA256:
- 964c385cd6d487ffdd120e9eb7602b61160406a9bcfd56b19877be5fc3533ea0
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