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 Settings

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
```

Plans for release of dataset or a newer more up to date version?

by ThiloteE - opened Nov 8, 2023

Discussion

ThiloteE

Nov 8, 2023

Karen_theEditor (https://huggingface.co/FPHam/Karen_theEditor-13B-4bit-128g-GPTQ)
Rachel_Assistant_Editor (https://huggingface.co/FPHam/Rachel_Assistant_Editor_13b_GPTQ)
Jackson_The_Formalizer (https://huggingface.co/FPHam/Jackson_The_Formalizer_V2_13b_GPTQ)

all have a very interesting theme and make them very attractive to people working in an office needing to release public statements or documentation. Are there any plans to release their datasets? Or at least a newer (quantized gguf) version of them, maybe with another and more up to date base model?

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