Text Generation
Transformers
Safetensors
mistral
conversational
custom_code
text-generation-inference
Instructions to use nocudaexe/Neural-Dark-Waifu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nocudaexe/Neural-Dark-Waifu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nocudaexe/Neural-Dark-Waifu", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("nocudaexe/Neural-Dark-Waifu", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("nocudaexe/Neural-Dark-Waifu", trust_remote_code=True) 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 nocudaexe/Neural-Dark-Waifu with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nocudaexe/Neural-Dark-Waifu" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nocudaexe/Neural-Dark-Waifu", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/nocudaexe/Neural-Dark-Waifu
- SGLang
How to use nocudaexe/Neural-Dark-Waifu 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 "nocudaexe/Neural-Dark-Waifu" \ --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": "nocudaexe/Neural-Dark-Waifu", "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 "nocudaexe/Neural-Dark-Waifu" \ --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": "nocudaexe/Neural-Dark-Waifu", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use nocudaexe/Neural-Dark-Waifu with Docker Model Runner:
docker model run hf.co/nocudaexe/Neural-Dark-Waifu
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
nocudaexe/Neural-Dark-Waifu-GGUF GGUF version
Potentially broken
Use: nocudaexe/Neural-Dark-Waifu-v0.2 tested to 15872 tokens
license: apache-2.0 tags: - merge - mergekit - lazymergekit - nocudaexe/Dark-Waifu-7b - nocudaexe/Infinite-Waifu
DarkNeural
DarkNeural is a merge of the following models using mergekit:
🧩 Configuration
```yamlmodels:
- model: Test157t/Kunocchini-7b-128k-test
No parameters necessary for base model
- model: nocudaexe/Dark-Waifu-7b parameters: density: 0.33 weight: 0.4
- model: nocudaexe/Infinite-Waifu parameters: density: 0.38 weight: 0.3 merge_method: dare_ties base_model: Test157t/Kunocchini-7b-128k-test parameters: int8_mask: true dtype: bfloat16 ```
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