Instructions to use TheBigBlender/LemonadeRP-4.5.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TheBigBlender/LemonadeRP-4.5.3 with Transformers:

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

pipe = pipeline("text-generation", model="TheBigBlender/LemonadeRP-4.5.3")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TheBigBlender/LemonadeRP-4.5.3")
model = AutoModelForCausalLM.from_pretrained("TheBigBlender/LemonadeRP-4.5.3", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TheBigBlender/LemonadeRP-4.5.3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TheBigBlender/LemonadeRP-4.5.3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TheBigBlender/LemonadeRP-4.5.3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/TheBigBlender/LemonadeRP-4.5.3

SGLang

How to use TheBigBlender/LemonadeRP-4.5.3 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 "TheBigBlender/LemonadeRP-4.5.3" \
    --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": "TheBigBlender/LemonadeRP-4.5.3",
		"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 "TheBigBlender/LemonadeRP-4.5.3" \
        --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": "TheBigBlender/LemonadeRP-4.5.3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TheBigBlender/LemonadeRP-4.5.3 with Docker Model Runner:
```
docker model run hf.co/TheBigBlender/LemonadeRP-4.5.3
```

Henk717 commited on Mar 1, 2024

Commit

8495cb6

verified ·

1 Parent(s): 7386cf1

Update README.md

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@@ -9,11 +9,11 @@ base_model:
 tags:
 - mergekit
 - merge
 ---
 # LemonadeRP-4.5.3
-This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
 ## Merge Details
 ### Merge Method
@@ -61,4 +61,4 @@ slices:
     model: tavtav/eros-7b-test
     parameters:
       weight: 0.18
-```

 tags:
 - mergekit
 - merge
+license: cc-by-nc-4.0
 ---
 # LemonadeRP-4.5.3
+This is a merge of pre-trained language models created by KatyTheCutie
 ## Merge Details
 ### Merge Method
     model: tavtav/eros-7b-test
     parameters:
       weight: 0.18
+```