Text Generation
Transformers
Safetensors
English
llama
text-generation-inference
unsloth
4-bit precision
Instructions to use shashikanth-a/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shashikanth-a/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="shashikanth-a/model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("shashikanth-a/model") model = AutoModelForCausalLM.from_pretrained("shashikanth-a/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use shashikanth-a/model with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "shashikanth-a/model" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "shashikanth-a/model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/shashikanth-a/model
- SGLang
How to use shashikanth-a/model 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 "shashikanth-a/model" \ --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": "shashikanth-a/model", "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 "shashikanth-a/model" \ --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": "shashikanth-a/model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Unsloth Desktop
- Docker Model Runner
How to use shashikanth-a/model with Docker Model Runner:
docker model run hf.co/shashikanth-a/model
Download tokenizer.json from shashikanth-a/model: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/shashikanth-a/model/resolve/main/tokenizer.json
- Command line
-
hf download hf://shashikanth-a/model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/shashikanth-a/model/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- f50a225d9f53b6d10de736023ad24fa9ce92634801004eb39d881f415a4784cb
- Size of remote file:
- 17.2 MB
- SHA256:
- 3c5cf44023714fb39b05e71e425f8d7b92805ff73f7988b083b8c87f0bf87393
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