Instructions to use solidrust/Llama-3-LewdPlay-8B-evo-AWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use solidrust/Llama-3-LewdPlay-8B-evo-AWQ with Transformers:

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

pipe = pipeline("text-generation", model="solidrust/Llama-3-LewdPlay-8B-evo-AWQ")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("solidrust/Llama-3-LewdPlay-8B-evo-AWQ")
model = AutoModelForCausalLM.from_pretrained("solidrust/Llama-3-LewdPlay-8B-evo-AWQ", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use solidrust/Llama-3-LewdPlay-8B-evo-AWQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "solidrust/Llama-3-LewdPlay-8B-evo-AWQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "solidrust/Llama-3-LewdPlay-8B-evo-AWQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/solidrust/Llama-3-LewdPlay-8B-evo-AWQ

SGLang

How to use solidrust/Llama-3-LewdPlay-8B-evo-AWQ 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 "solidrust/Llama-3-LewdPlay-8B-evo-AWQ" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "solidrust/Llama-3-LewdPlay-8B-evo-AWQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "solidrust/Llama-3-LewdPlay-8B-evo-AWQ" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "solidrust/Llama-3-LewdPlay-8B-evo-AWQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use solidrust/Llama-3-LewdPlay-8B-evo-AWQ with Docker Model Runner:
```
docker model run hf.co/solidrust/Llama-3-LewdPlay-8B-evo-AWQ
```

Suparious commited on Sep 3, 2024

Commit

e6e1798

verified ·

1 Parent(s): 7e254ac

Updated and moved existing to merged_models base_model tag in README.md

Browse files

Files changed (1) hide show

README.md +6 -5

README.md CHANGED Viewed

@@ -1,10 +1,14 @@
 ---
 license: cc-by-nc-4.0
-base_model:
 - vicgalle/Roleplay-Llama-3-8B
 - Undi95/Llama-3-Unholy-8B-e4
 - Undi95/Llama-3-LewdPlay-8B
-library_name: transformers
 tags:
 - mergekit
 - merge
@@ -13,9 +17,6 @@ tags:
 - text-generation
 - autotrain_compatible
 - endpoints_compatible
-pipeline_tag: text-generation
-inference: false
-quantized_by: Suparious
 ---
 # Undi95/Llama-3-LewdPlay-8B-evo AWQ

 ---
+base_model: Undi95/Llama-3-LewdPlay-8B-evo
+inference: false
+library_name: transformers
 license: cc-by-nc-4.0
+merged_models:
 - vicgalle/Roleplay-Llama-3-8B
 - Undi95/Llama-3-Unholy-8B-e4
 - Undi95/Llama-3-LewdPlay-8B
+pipeline_tag: text-generation
+quantized_by: Suparious
 tags:
 - mergekit
 - merge
 - text-generation
 - autotrain_compatible
 - endpoints_compatible
 ---
 # Undi95/Llama-3-LewdPlay-8B-evo AWQ