Instructions to use fhai50032/RolePlayLake-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use fhai50032/RolePlayLake-7B with Transformers:

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

pipe = pipeline("text-generation", model="fhai50032/RolePlayLake-7B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("fhai50032/RolePlayLake-7B")
model = AutoModelForCausalLM.from_pretrained("fhai50032/RolePlayLake-7B", device_map="auto")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use fhai50032/RolePlayLake-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "fhai50032/RolePlayLake-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fhai50032/RolePlayLake-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/fhai50032/RolePlayLake-7B

SGLang

How to use fhai50032/RolePlayLake-7B 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 "fhai50032/RolePlayLake-7B" \
    --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": "fhai50032/RolePlayLake-7B",
		"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 "fhai50032/RolePlayLake-7B" \
        --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": "fhai50032/RolePlayLake-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use fhai50032/RolePlayLake-7B with Docker Model Runner:
```
docker model run hf.co/fhai50032/RolePlayLake-7B
```

fhai50032 commited on Jan 30, 2024

Commit

0672005

verified ·

1 Parent(s): 41228fe

Update README.md

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README.md CHANGED Viewed

@@ -17,6 +17,14 @@ RolePlayLake-7B is a merge of the following models :
 * [SanjiWatsuki/Silicon-Maid-7B](https://huggingface.co/SanjiWatsuki/Silicon-Maid-7B)
 * [senseable/WestLake-7B-v2](https://huggingface.co/senseable/WestLake-7B-v2)
 ## 🧩 Configuration
 ```yaml

 * [SanjiWatsuki/Silicon-Maid-7B](https://huggingface.co/SanjiWatsuki/Silicon-Maid-7B)
 * [senseable/WestLake-7B-v2](https://huggingface.co/senseable/WestLake-7B-v2)
+ `In my current testing RolePlayLake is Better than Silicon_Maid in RP and More Uncensored Than WestLake`
+`I would try to only merge Uncensored Models with Baising towards Chat rather than Instruct `
 ## 🧩 Configuration
 ```yaml