Triangle104/Roleplay-Hermes-3-Llama-3.1-8B-Q5_K_S-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.
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.
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-Q5_K_S-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q5_k_s.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Triangle104/Roleplay-Hermes-3-Llama-3.1-8B-Q5_K_S-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q5_k_s.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-Q5_K_S-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q5_k_s.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Triangle104/Roleplay-Hermes-3-Llama-3.1-8B-Q5_K_S-GGUF --hf-file roleplay-hermes-3-llama-3.1-8b-q5_k_s.gguf -c 2048
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Base model
vicgalle/Roleplay-Hermes-3-Llama-3.1-8B