Instructions to use buddhist-nlp/gemma-2-mitra-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use buddhist-nlp/gemma-2-mitra-it with Transformers:

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

pipe = pipeline("text-generation", model="buddhist-nlp/gemma-2-mitra-it")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("buddhist-nlp/gemma-2-mitra-it")
model = AutoModelForCausalLM.from_pretrained("buddhist-nlp/gemma-2-mitra-it", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use buddhist-nlp/gemma-2-mitra-it with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "buddhist-nlp/gemma-2-mitra-it"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "buddhist-nlp/gemma-2-mitra-it",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/buddhist-nlp/gemma-2-mitra-it

SGLang

How to use buddhist-nlp/gemma-2-mitra-it 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 "buddhist-nlp/gemma-2-mitra-it" \
    --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": "buddhist-nlp/gemma-2-mitra-it",
		"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 "buddhist-nlp/gemma-2-mitra-it" \
        --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": "buddhist-nlp/gemma-2-mitra-it",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use buddhist-nlp/gemma-2-mitra-it with Docker Model Runner:
```
docker model run hf.co/buddhist-nlp/gemma-2-mitra-it
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

gemma2-mitra-it

This is based on gemma2-mitra-base and finetuned on Translation instructions. The template for prompting the model is this:

Please translate into <target_language>: <input_sentence> 🔽 Translation::

Line breaks in this model should be replaced with the '🔽' character before running the generation. '#' is used as a stop token.

Model Details

For details on how to run this please see the gemma2-9b repository: https://huggingface.co/google/gemma-2-9b

Downloads last month: 181

Safetensors

Model size

9B params

Tensor type

F32

Model tree for buddhist-nlp/gemma-2-mitra-it

Adapters

2 models

Quantizations

3 models

Collection including buddhist-nlp/gemma-2-mitra-it

Gemma-2 Mitra (2024)

Collection

The first-generation Dharmamitra model family (trained August 2024) on gemma-2: base, instruct, embedder — plus the 2026 chat SFT. • 7 items • Updated 2 days ago