Instructions to use FreedomIntelligence/ALLaVA-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FreedomIntelligence/ALLaVA-3B with Transformers:

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

pipe = pipeline("text-generation", model="FreedomIntelligence/ALLaVA-3B", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/ALLaVA-3B", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use FreedomIntelligence/ALLaVA-3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FreedomIntelligence/ALLaVA-3B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FreedomIntelligence/ALLaVA-3B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/FreedomIntelligence/ALLaVA-3B

SGLang

How to use FreedomIntelligence/ALLaVA-3B 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 "FreedomIntelligence/ALLaVA-3B" \
    --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": "FreedomIntelligence/ALLaVA-3B",
		"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 "FreedomIntelligence/ALLaVA-3B" \
        --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": "FreedomIntelligence/ALLaVA-3B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use FreedomIntelligence/ALLaVA-3B with Docker Model Runner:
```
docker model run hf.co/FreedomIntelligence/ALLaVA-3B
```

g-h-chen commited on Feb 29, 2024

Commit

570e8c5

verified ·

1 Parent(s): 1bbfd18

Delete constants.py with huggingface_hub

Browse files

Files changed (1) hide show

constants.py +0 -13

constants.py DELETED Viewed

@@ -1,13 +0,0 @@
-CONTROLLER_HEART_BEAT_EXPIRATION = 30
-WORKER_HEART_BEAT_INTERVAL = 15
-LOGDIR = "."
-# Model Constants
-IGNORE_INDEX = -100
-IMAGE_TOKEN_INDEX = -200
-DEFAULT_IMAGE_TOKEN = "<image>"
-DEFAULT_IMAGE_PATCH_TOKEN = "<im_patch>"
-DEFAULT_IM_START_TOKEN = "<im_start>"
-DEFAULT_IM_END_TOKEN = "<im_end>"
-IMAGE_PLACEHOLDER = "<image-placeholder>"