Models / Chat / Gemma Instruct (2B)
Gemma Instruct (2B)
LLM
2B instruct Gemma model by Google: lightweight, open, text-to-text LLM for QA, summarization, reasoning, and resource-efficient deployment.
Try our Gemma API
API Usage
How to use Gemma Instruct (2B)Model CardPrompting Gemma Instruct (2B)Applications & Use CasesAPI Usage
Endpoint
google/gemma-2b-it
RUN INFERENCE
curl -X POST "https://api.together.xyz/v1/chat/completions" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "google/gemma-2b-it",
"messages": [{"role": "user", "content": "What are some fun things to do in New York?"}]
}'
JSON RESPONSE
RUN INFERENCE
from together import Together
client = Together()
response = client.chat.completions.create(
model="google/gemma-2b-it",
messages=[{"role": "user", "content": "What are some fun things to do in New York?"}],
)
print(response.choices[0].message.content)
JSON RESPONSE
RUN INFERENCE
import Together from "together-ai";
const together = new Together();
const response = await together.chat.completions.create({
messages: [{"role": "user", "content": "What are some fun things to do in New York?"}],
model: "google/gemma-2b-it",
});
console.log(response.choices[0].message.content)
JSON RESPONSE
Model Provider:
Type:
Chat
Variant:
Instruct
Parameters:
2B
Deployment:
✔ Serverless ✔ Dedicated
Quantization
FP16
Context length:
8K
Pricing:
$0.10
Run in playground
Deploy model
Quickstart docs
Quickstart docs
How to use Gemma Instruct (2B)
Model details
Prompting Gemma Instruct (2B)
Applications & Use Cases
Looking for production scale? Deploy on a dedicated endpoint
Deploy Gemma Instruct (2B) on a dedicated endpoint with custom hardware configuration, as many instances as you need, and auto-scaling.
