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

Libraries

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

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

pipe = pipeline("text-generation", model="IndexTeam/Index-1.9B-Constant-LR", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("IndexTeam/Index-1.9B-Constant-LR", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use IndexTeam/Index-1.9B-Constant-LR 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-Constant-LR"
# 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-Constant-LR",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

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

SGLang

How to use IndexTeam/Index-1.9B-Constant-LR 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-Constant-LR" \
    --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-Constant-LR",
		"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-Constant-LR" \
        --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-Constant-LR",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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

AsirAsir commited on Jun 26, 2024

Commit

9e0d0bb

verified ·

1 Parent(s): 2606635

Upload README.md

Browse files

Files changed (1) hide show

README.md +25 -0

README.md ADDED Viewed

	@@ -0,0 +1,25 @@

+---
+license: other
+license_name: license
+license_link: LICENSE
+---
+<div align="center">
+<h1>
+  Index-1.9B-Constant-LR
+</h1>
+</div>
+## Model Introduction
+This repository Index-1.9B-Constant-LR is the checkpoint file of the [Index-1.9B](https://huggingface.co/IndexTeam/Index-1.9B) base model before decay training, which is provided for everyone to conduct research on downstream tasks.
+For more details, see our [GitHub](https://github.com/bilibili/Index-1.9B) and [Index-1.9B Technical Report](https://github.com/bilibili/Index-1.9B/blob/main/Index-1.9B%20%E6%8A%80%E6%9C%AF%E6%8A%A5%E5%91%8A.pdf)
+## Evaluation Results
+Here we add the evaluation of the general understanding ability of the Index-1.9B-Constant-LR model
+|Model|Average score|Average English score|MMLU|CEVAL|CMMLU|HellaSwag|Arc-C|Arc-E|
+|----|----|----|----|----|----|----|----|----|
+|**Index-1.9B-Constant-LR**|41.47 |44.24 |35.30|38.58|33.26|59.94|32.96|48.75|
+|**Index-1.9B-Pure**|49.55 |52.83 |43.75|42.35|43.61|63.21|42.75|61.61|
+|**Index-1.9B**|**64.92** |**69.93**|52.53|57.01|52.79|80.69|65.15|81.35|
+Evaluation code is based on [OpenCompass](https://github.com/open-compass/opencompass) with compatibility modifications. See the [evaluate](./evaluate/) folder for details.