Instructions to use IndexTeam/Index-1.9B-Pure with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IndexTeam/Index-1.9B-Pure with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="IndexTeam/Index-1.9B-Pure", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("IndexTeam/Index-1.9B-Pure", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use IndexTeam/Index-1.9B-Pure 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-Pure" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "IndexTeam/Index-1.9B-Pure", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/IndexTeam/Index-1.9B-Pure
- SGLang
How to use IndexTeam/Index-1.9B-Pure 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-Pure" \ --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": "IndexTeam/Index-1.9B-Pure", "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 "IndexTeam/Index-1.9B-Pure" \ --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": "IndexTeam/Index-1.9B-Pure", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use IndexTeam/Index-1.9B-Pure with Docker Model Runner:
docker model run hf.co/IndexTeam/Index-1.9B-Pure
Add pipeline tag, library name, and paper link to model card
#2
by nielsr HF Staff - opened
README.md
CHANGED
|
@@ -2,7 +2,10 @@
|
|
| 2 |
license: other
|
| 3 |
license_name: license
|
| 4 |
license_link: LICENSE
|
|
|
|
|
|
|
| 5 |
---
|
|
|
|
| 6 |
<div align="center">
|
| 7 |
<h1>
|
| 8 |
Index-1.9B
|
|
@@ -22,7 +25,7 @@ We are excited to announce the release of a lightweight version from the Index s
|
|
| 22 |
- For the **Chat model**, see [Index-1.9B-Chat](https://huggingface.co/IndexTeam/Index-1.9B-Chat)
|
| 23 |
- For the **Role-playing model**, see [Index-1.9B-Character](https://huggingface.co/IndexTeam/Index-1.9B-Character)
|
| 24 |
|
| 25 |
-
For more details, see our [GitHub](https://github.com/bilibili/Index-1.9B) and [Index
|
| 26 |
|
| 27 |
## Evaluation Results
|
| 28 |
The Index-1.9B shows excellent performance in general understanding evaluations, leading compared to recently open-sourced small models and comparable to some 7B and models larger than 10B.
|
|
@@ -43,6 +46,4 @@ The Index-1.9B shows excellent performance in general understanding evaluations,
|
|
| 43 |
|MPT-30B (report)|/|63.48|46.9|/|/|79.9|50.6|76.5|
|
| 44 |
|Falcon-40B (report)|/|68.18|55.4|/|/|83.6|54.5|79.2|
|
| 45 |
|
| 46 |
-
Evaluation code is based on [OpenCompass](https://github.com/open-compass/opencompass) with compatibility modifications. See the [evaluate](./evaluate/) folder for details.
|
| 47 |
-
|
| 48 |
-
|
|
|
|
| 2 |
license: other
|
| 3 |
license_name: license
|
| 4 |
license_link: LICENSE
|
| 5 |
+
pipeline_tag: text-generation
|
| 6 |
+
library_name: transformers
|
| 7 |
---
|
| 8 |
+
|
| 9 |
<div align="center">
|
| 10 |
<h1>
|
| 11 |
Index-1.9B
|
|
|
|
| 25 |
- For the **Chat model**, see [Index-1.9B-Chat](https://huggingface.co/IndexTeam/Index-1.9B-Chat)
|
| 26 |
- For the **Role-playing model**, see [Index-1.9B-Character](https://huggingface.co/IndexTeam/Index-1.9B-Character)
|
| 27 |
|
| 28 |
+
For more details, see our [GitHub](https://github.com/bilibili/Index-1.9B) and the [Index SLM Technical Report](https://huggingface.co/papers/2607.09885).
|
| 29 |
|
| 30 |
## Evaluation Results
|
| 31 |
The Index-1.9B shows excellent performance in general understanding evaluations, leading compared to recently open-sourced small models and comparable to some 7B and models larger than 10B.
|
|
|
|
| 46 |
|MPT-30B (report)|/|63.48|46.9|/|/|79.9|50.6|76.5|
|
| 47 |
|Falcon-40B (report)|/|68.18|55.4|/|/|83.6|54.5|79.2|
|
| 48 |
|
| 49 |
+
Evaluation code is based on [OpenCompass](https://github.com/open-compass/opencompass) with compatibility modifications. See the [evaluate](./evaluate/) folder for details.
|
|
|
|
|
|