Instructions to use aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K with Transformers:

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

pipe = pipeline("text-generation", model="aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K")
model = AutoModelForCausalLM.from_pretrained("aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K")

Inference
Local Apps Settings

vLLM

How to use aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K

SGLang

How to use aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K 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 "aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K" \
    --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": "aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K",
		"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 "aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K" \
        --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": "aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K with Docker Model Runner:
```
docker model run hf.co/aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K
```

aifeifei798 commited on Jul 1, 2024

Commit

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@@ -87,8 +87,9 @@ The module combination has been readjusted to better fulfill various roles and h
     ],
 ```
 # Model Use
-- Koboldcpp https://github.com/LostRuins/koboldcpp
 - Since KoboldCpp is taking a while to update with the latest llama.cpp commits, I'll recommend this [fork](https://github.com/Nexesenex/kobold.cpp) if anyone has issues.
 - LM Studio https://lmstudio.ai/
 - llama.cpp https://github.com/ggerganov/llama.cpp
 - Backyard AI https://backyard.ai/

     ],
 ```
 # Model Use
+- Koboldcpp https://github.com/Nexesenex/kobold.cpp
 - Since KoboldCpp is taking a while to update with the latest llama.cpp commits, I'll recommend this [fork](https://github.com/Nexesenex/kobold.cpp) if anyone has issues.
+- text-generation-webui https://github.com/oobabooga/text-generation-webui
 - LM Studio https://lmstudio.ai/
 - llama.cpp https://github.com/ggerganov/llama.cpp
 - Backyard AI https://backyard.ai/