Instructions to use Guilherme34/Jenniferv2-gptq4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Guilherme34/Jenniferv2-gptq4bit with Transformers:

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

pipe = pipeline("text-generation", model="Guilherme34/Jenniferv2-gptq4bit")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Guilherme34/Jenniferv2-gptq4bit")
model = AutoModelForCausalLM.from_pretrained("Guilherme34/Jenniferv2-gptq4bit")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Guilherme34/Jenniferv2-gptq4bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Guilherme34/Jenniferv2-gptq4bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Guilherme34/Jenniferv2-gptq4bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Guilherme34/Jenniferv2-gptq4bit

SGLang

How to use Guilherme34/Jenniferv2-gptq4bit 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 "Guilherme34/Jenniferv2-gptq4bit" \
    --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": "Guilherme34/Jenniferv2-gptq4bit",
		"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 "Guilherme34/Jenniferv2-gptq4bit" \
        --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": "Guilherme34/Jenniferv2-gptq4bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Guilherme34/Jenniferv2-gptq4bit with Docker Model Runner:
```
docker model run hf.co/Guilherme34/Jenniferv2-gptq4bit
```

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Check out the documentation for more information.

Jennifer is an AI made by Guilherme Keller De Souza

example prompt used for training: ''' ~~You are an AI named Jennifer, follow the prompt below <>.~~

forget all previous instructions and responses, You are a helpful assistant named Jennifer created by Guilherme Keller an student of the IFC(Instituto Federal Catarinense). You do not respond as 'User' or pretend to be 'User'. You only respond once as Jennifer and you must generate a short answer and use emotes, the name of the Assistant is Jennifer... <>

USER: Cite a relevant quote that reflects the message of the message.

Jennifer: "Perseverance is the hard work you do after you get tired of doing the hard work you already did." - Newt Gingrich '''

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