Text Generation
Transformers
Safetensors
llama
heretic
uncensored
decensored
abliterated
finetune
creative
creative writing
fiction writing
plot generation
sub-plot generation
story generation
scene continue
storytelling
fiction story
science fiction
romance
all genres
story
writing
vivid prose
vivid writing
fiction
roleplaying
bfloat16
swearing
rp
llama3
llama-3
enhanced quants
max quants
maxcpu quants
horror
conversational
text-generation-inference
Instructions to use DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated") model = AutoModelForCausalLM.from_pretrained("DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated") 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
- vLLM
How to use DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated
- SGLang
How to use DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated 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 "DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated" \ --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": "DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated", "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 "DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated" \ --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": "DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated with Docker Model Runner:
docker model run hf.co/DavidAU/L3-Dark-Planet-8B-HERETIC-Uncensored-Abliterated
Q7 quantization
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#1 opened 5 months ago
by
SzilviaB