Text Generation
Transformers
PyTorch
Safetensors
Hindi
English
multilingual
gpt2
codemix
text-generation-inference
Instructions to use l3cube-pune/hing-gpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/hing-gpt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="l3cube-pune/hing-gpt")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/hing-gpt") model = AutoModelForCausalLM.from_pretrained("l3cube-pune/hing-gpt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use l3cube-pune/hing-gpt with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "l3cube-pune/hing-gpt" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "l3cube-pune/hing-gpt", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/l3cube-pune/hing-gpt
- SGLang
How to use l3cube-pune/hing-gpt 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 "l3cube-pune/hing-gpt" \ --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": "l3cube-pune/hing-gpt", "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 "l3cube-pune/hing-gpt" \ --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": "l3cube-pune/hing-gpt", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use l3cube-pune/hing-gpt with Docker Model Runner:
docker model run hf.co/l3cube-pune/hing-gpt
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Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (597c1c8d595e2ffc204864192600bb0d9b6922c0) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>91df3f7
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Add multilingual to the language tag (#1)
- Add multilingual to the language tag (d327dc4da751c69cadb823b235de1e80d0fc6249) Co-authored-by: Loïck BOURDOIS <lbourdois@users.noreply.huggingface.co>ce7df41
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