Instructions to use FPHam/Rachel_Assistant_Editor_13b_GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FPHam/Rachel_Assistant_Editor_13b_GPTQ with Transformers:

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

pipe = pipeline("text-generation", model="FPHam/Rachel_Assistant_Editor_13b_GPTQ")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("FPHam/Rachel_Assistant_Editor_13b_GPTQ")
model = AutoModelForCausalLM.from_pretrained("FPHam/Rachel_Assistant_Editor_13b_GPTQ")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use FPHam/Rachel_Assistant_Editor_13b_GPTQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FPHam/Rachel_Assistant_Editor_13b_GPTQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FPHam/Rachel_Assistant_Editor_13b_GPTQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/FPHam/Rachel_Assistant_Editor_13b_GPTQ

SGLang

How to use FPHam/Rachel_Assistant_Editor_13b_GPTQ 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 "FPHam/Rachel_Assistant_Editor_13b_GPTQ" \
    --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": "FPHam/Rachel_Assistant_Editor_13b_GPTQ",
		"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 "FPHam/Rachel_Assistant_Editor_13b_GPTQ" \
        --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": "FPHam/Rachel_Assistant_Editor_13b_GPTQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use FPHam/Rachel_Assistant_Editor_13b_GPTQ with Docker Model Runner:
```
docker model run hf.co/FPHam/Rachel_Assistant_Editor_13b_GPTQ
```

When we will get Jessica_Content_Creator?

by photogbill40 - opened Jul 14, 2023

Discussion

photogbill40

Jul 14, 2023

Jessica is like that person who doodles notes inside text books adding additional detail, fleshing out stories with more content, or just adding footnotes explaining various parts of the plot at the bottom of a story. Just an idea.

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