Instructions to use tarekziade/test-quantize with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tarekziade/test-quantize with Transformers:

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

pipe = pipeline("image-text-to-text", model="tarekziade/test-quantize")

# Load model directly
from transformers import AutoTokenizer, AutoModelForImageTextToText

tokenizer = AutoTokenizer.from_pretrained("tarekziade/test-quantize")
model = AutoModelForImageTextToText.from_pretrained("tarekziade/test-quantize")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use tarekziade/test-quantize with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/tarekziade/test-quantize

SGLang

How to use tarekziade/test-quantize 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 "tarekziade/test-quantize" \
    --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": "tarekziade/test-quantize",
		"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 "tarekziade/test-quantize" \
        --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": "tarekziade/test-quantize",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use tarekziade/test-quantize with Docker Model Runner:
```
docker model run hf.co/tarekziade/test-quantize
```

tarekziade HF Staff commited on Jun 5, 2024

Commit

bf79707

verified ·

1 Parent(s): 3e48f83

Update generation_config.json

Browse files

Files changed (1) hide show

generation_config.json +3 -2

generation_config.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "bos_token_id": 50256,
-  "do_sample": true,
   "early_stopping": true,
   "eos_token_id": 50256,
   "max_length": 50,
@@ -8,5 +8,6 @@
   "num_beams": 4,
   "pad_token_id": 50256,
   "repetition_penalty": 1.2,
-  "transformers_version": "4.33.2"
 }

 {
   "bos_token_id": 50256,
+  "do_sample": false,
   "early_stopping": true,
   "eos_token_id": 50256,
   "max_length": 50,
   "num_beams": 4,
   "pad_token_id": 50256,
   "repetition_penalty": 1.2,
+  "transformers_version": "4.33.2",
+  "seed": 42
 }