Instructions to use invocation02/test_9_resid_post with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use invocation02/test_9_resid_post with Transformers:

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

pipe = pipeline("text-generation", model="invocation02/test_9_resid_post")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("invocation02/test_9_resid_post")
model = AutoModelForCausalLM.from_pretrained("invocation02/test_9_resid_post")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use invocation02/test_9_resid_post with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "invocation02/test_9_resid_post"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "invocation02/test_9_resid_post",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/invocation02/test_9_resid_post

SGLang

How to use invocation02/test_9_resid_post 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 "invocation02/test_9_resid_post" \
    --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": "invocation02/test_9_resid_post",
		"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 "invocation02/test_9_resid_post" \
        --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": "invocation02/test_9_resid_post",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use invocation02/test_9_resid_post with Docker Model Runner:
```
docker model run hf.co/invocation02/test_9_resid_post
```

[WIP] Upload folder using huggingface_hub (multi-commit 0bddbfd65fdf9eaf5b462c87083fb753ea2f67b0f5ba1a6c606113d54f7e2e8d)

by invocation02 - opened May 15, 2024

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

-348

This PR is in draft mode

invocation02

Owner May 15, 2024

Upload folder using huggingface_hub

Multi commit ID: 0bddbfd65fdf9eaf5b462c87083fb753ea2f67b0f5ba1a6c606113d54f7e2e8d

Scheduled commits:

Upload 1 file(s) totalling 5.0G (d96ba0dd38ac77e4b490e1822fa50bfa023097c45d3cb71a49ca01be39650168)
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