Text Generation
Transformers
Safetensors
English
Telugu
Sanskrit
deepseek_v3
multilingual
fine-tuned
deepseek
entity-extraction
text-generation-inference
Instructions to use asrith05/slm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asrith05/slm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="asrith05/slm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("asrith05/slm") model = AutoModelForCausalLM.from_pretrained("asrith05/slm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use asrith05/slm with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "asrith05/slm" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "asrith05/slm", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/asrith05/slm
- SGLang
How to use asrith05/slm 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 "asrith05/slm" \ --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": "asrith05/slm", "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 "asrith05/slm" \ --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": "asrith05/slm", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use asrith05/slm with Docker Model Runner:
docker model run hf.co/asrith05/slm
Download scaler.pt from asrith05/slm: direct link, hf CLI and curl.
- Browser
- Download file 988 Bytes
-
https://huggingface.co/asrith05/slm/resolve/main/scaler.pt
- Command line
-
hf download hf://asrith05/slm/scaler.pt
-
curl -L -o scaler.pt https://huggingface.co/asrith05/slm/resolve/main/scaler.pt
988 Bytes
- Xet hash:
- a08657a7920f6914d36e8e4bfb9cfefdf2897a387288bfca2ffb4c52c003ce18
- Size of remote file:
- 988 Bytes
- SHA256:
- badc63cec424a89fb7dfe663263eeda22f6a2d0d8a4dd4de5e321e742a6e55be
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