Instructions to use shreethar/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use shreethar/model with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="shreethar/model")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("shreethar/model")
model = AutoModelForCausalLM.from_pretrained("shreethar/model")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use shreethar/model with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "shreethar/model"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "shreethar/model",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/shreethar/model

SGLang

How to use shreethar/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 "shreethar/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": "shreethar/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 "shreethar/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": "shreethar/model",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Unsloth Studio

How to use shreethar/model with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for shreethar/model to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for shreethar/model to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for shreethar/model to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="shreethar/model",
    max_seq_length=2048,
)

Docker Model Runner
How to use shreethar/model with Docker Model Runner:
```
docker model run hf.co/shreethar/model
```

model

Commit History

(Trained with Unsloth)

42b1918
verified

Shreethar Raveenthar commited on Jul 1, 2025

(Trained with Unsloth)

69038d4
verified

Shreethar Raveenthar commited on Jul 1, 2025

Unsloth Model Card

daa8aac
verified

Shreethar Raveenthar commited on Jul 1, 2025

initial commit

ee31d4d
verified

Shreethar Raveenthar commited on Jul 1, 2025

Commit History

(Trained with Unsloth) 42b1918 verified

(Trained with Unsloth) 69038d4 verified

Unsloth Model Card daa8aac verified

initial commit ee31d4d verified

(Trained with Unsloth)

42b1918
verified

(Trained with Unsloth)

69038d4
verified

Unsloth Model Card

daa8aac
verified

initial commit

ee31d4d
verified