Text Generation
Transformers
Safetensors
Sindhi
gpt2
Computational_linguistics
Low_resouce_Language
LLM
GPT
text-generation-inference
Instructions to use aakashMeghwar01/SindhiLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aakashMeghwar01/SindhiLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="aakashMeghwar01/SindhiLM")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("aakashMeghwar01/SindhiLM") model = AutoModelForCausalLM.from_pretrained("aakashMeghwar01/SindhiLM") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use aakashMeghwar01/SindhiLM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "aakashMeghwar01/SindhiLM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "aakashMeghwar01/SindhiLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/aakashMeghwar01/SindhiLM
- SGLang
How to use aakashMeghwar01/SindhiLM 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 "aakashMeghwar01/SindhiLM" \ --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": "aakashMeghwar01/SindhiLM", "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 "aakashMeghwar01/SindhiLM" \ --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": "aakashMeghwar01/SindhiLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use aakashMeghwar01/SindhiLM with Docker Model Runner:
docker model run hf.co/aakashMeghwar01/SindhiLM
File size: 457 Bytes
59c2a98 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"backend": "tokenizers",
"is_local": true,
"max_length": 512,
"model_max_length": 512,
"pad_to_multiple_of": null,
"pad_token": "<|pad|>",
"pad_token_type_id": 0,
"padding_side": "right",
"special_tokens": {
"eos": "<|endoftext|>",
"pad": "<|pad|>",
"unk": "<|unk|>"
},
"stride": 0,
"tokenizer_class": "TokenizersBackend",
"truncation_side": "right",
"truncation_strategy": "longest_first",
"vocab_size": 24000
}
|