Instructions to use nocudaexe/Infinite-Waifu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nocudaexe/Infinite-Waifu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nocudaexe/Infinite-Waifu") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("nocudaexe/Infinite-Waifu") model = AutoModelForCausalLM.from_pretrained("nocudaexe/Infinite-Waifu", 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=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use nocudaexe/Infinite-Waifu with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nocudaexe/Infinite-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/Infinite-Waifu", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/nocudaexe/Infinite-Waifu
- SGLang
How to use nocudaexe/Infinite-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/Infinite-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/Infinite-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/Infinite-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/Infinite-Waifu", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use nocudaexe/Infinite-Waifu with Docker Model Runner:
docker model run hf.co/nocudaexe/Infinite-Waifu
Commit History
-
Update README.md
Verified signature3e3ebf8 -
Update README.md
Verified signature54c562f
-
Update README.md
Verified signature Basically, I took an excellent chat llm that has some weird hangups in RP, and merged it with a bunch of ERP models --- base_model: - Endevor/InfinityRP-v1-7B - Test157t/Kunocchini-7b-128k-test - mlabonne/AlphaMonarch-7B - KatyTheCutie/SlushySlerp-7B library_name: transformers tags: - mergekit - merge --- # merge This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). ## Merge Details ### Merge Method This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B) as a base. ### Models Merged The following models were included in the merge: * [Endevor/InfinityRP-v1-7B](https://huggingface.co/Endevor/InfinityRP-v1-7B) * [Test157t/Kunocchini-7b-128k…b569272 -
Update README.md
Verified signature52f66e0 -
Upload 16 files
Verified signature974fe4f -
initial commit
Verified signature2dffbad