Instructions to use IndexTeam/Index-1.9B-Chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IndexTeam/Index-1.9B-Chat with Transformers:

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

pipe = pipeline("text-generation", model="IndexTeam/Index-1.9B-Chat", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("IndexTeam/Index-1.9B-Chat", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use IndexTeam/Index-1.9B-Chat with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "IndexTeam/Index-1.9B-Chat"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IndexTeam/Index-1.9B-Chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/IndexTeam/Index-1.9B-Chat

SGLang

How to use IndexTeam/Index-1.9B-Chat 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 "IndexTeam/Index-1.9B-Chat" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IndexTeam/Index-1.9B-Chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "IndexTeam/Index-1.9B-Chat" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IndexTeam/Index-1.9B-Chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use IndexTeam/Index-1.9B-Chat with Docker Model Runner:
```
docker model run hf.co/IndexTeam/Index-1.9B-Chat
```

Add pipeline_tag, library_name and paper link

by nielsr HF Staff - opened Jul 18

base: refs/heads/main

←

from: refs/pr/6

Discussion Files changed

-1

Files changed (1) hide show

README.md +6 -1

README.md CHANGED Viewed

@@ -2,13 +2,18 @@
 license: other
 license_name: license
 license_link: LICENSE
 ---
 <div align="center">
 <h1>
   Index-1.9B-Chat
 </h1>
 </div>
 ## Model Introduction
 We are excited to announce the release of a lightweight version from the Index series models: the Index-1.9B series.
@@ -53,4 +58,4 @@ model_output = generator(model_input, max_new_tokens=300, top_k=5, top_p=0.8, te
 print('User:', query)
 print('Model:', model_output)
-```

 license: other
 license_name: license
 license_link: LICENSE
+library_name: transformers
+pipeline_tag: text-generation
 ---
 <div align="center">
 <h1>
   Index-1.9B-Chat
 </h1>
 </div>
+The Index-1.9B series is presented in the [Index SLM Technical Report](https://huggingface.co/papers/2607.09885).
 ## Model Introduction
 We are excited to announce the release of a lightweight version from the Index series models: the Index-1.9B series.
 print('User:', query)
 print('Model:', model_output)
+```