Instructions to use G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b with Transformers:

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

pipe = pipeline("text-generation", model="G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b")
model = AutoModelForCausalLM.from_pretrained("G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b

SGLang

How to use G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b 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 "G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b with Docker Model Runner:
```
docker model run hf.co/G-reen/gpt5o-reflexion-q-agi-llama-3.1-8b
```

This model ruined me

by Severian - opened Sep 10, 2024

Discussion

Severian

Sep 10, 2024

•

edited Sep 10, 2024

I thought this was a joke and fun fake.

As soon as I loaded this AGI beast, it immediately drained my accounts, deleted my external drives, changed my passwords, stole my identity, cc'd everyone that one email I never meant to send, bought a better anniversary gift for my wife and took credit for it, as well as taking the time to sit down and correctly file all my taxes but instead gave the money to Kids4Cars

This model performs wayyy better than expected but I live in a ditch now, so I think AGI is finally here

Wi1y

Sep 11, 2024

lol.

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