Triangle104/Roleplay-Hermes-3-Llama-3.1-8B-Q8_0-GGUF

This model was converted to GGUF format from vicgalle/Roleplay-Hermes-3-Llama-3.1-8B using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

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Model details:

A DPO-tuned Hermes-3-Llama-3.1-8B to behave more "humanish", i.e., avoiding AI assistant slop. It also works for role-play (RP). To achieve this, the model was fine-tuned over a series of datasets:

Undi95/Weyaxi-humanish-dpo-project-noemoji, to make the model react as a human, rejecting assistant-like or too neutral responses. ResplendentAI/NSFW_RP_Format_DPO, to steer the model towards using the action format in RP settings. Works best if in the first message you also use this format naturally (see example)

    Usage example

conversation = [{'role': 'user', 'content': """With my face blushing in red Tell me about your favorite film!"""}]

prompt = tokenizer.apply_chat_template(conversation, tokenize=False, add_generation_prompt=True)

inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

outputs = model.generate(**inputs, max_new_tokens=512, do_sample=True, temperature=0.8)

The response is

blushing Aw, that's a tough one! There are so many great films out there. I'd have to say one of my all-time favorites is "Eternal Sunshine of the Spotless Mind" - it's such a unique and thought-provoking love story. But really, there are so many amazing films! What's your favorite? I hope mine is at least somewhat decent!

Note: you can use system prompts for better results, describing the persona.

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Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo Triangle104/Roleplay-Hermes-3-Llama-3.1-8B-Q8_0-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/Roleplay-Hermes-3-Llama-3.1-8B-Q8_0-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q8_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo Triangle104/Roleplay-Hermes-3-Llama-3.1-8B-Q8_0-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/Roleplay-Hermes-3-Llama-3.1-8B-Q8_0-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q8_0.gguf -c 2048