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Triangle104/Llama3.1-Allades-8B-Q4_K_M-GGUF

This model was converted to GGUF format from nbeerbower/Llama3.1-Allades-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:

Allades finetunes abliterated Llama 3.1 with 5 datasets to improve creative writing, reasoning, and roleplay. Datasets

jondurbin/gutenberg-dpo-v0.1
nbeerbower/gutenberg2-dpo
jondurbin/truthy-dpo-v0.1
kyujinpy/orca_math_dpo
antiven0m/physical-reasoning-dpo

Training

ORPO tuned for 1 epoch with 2x RTX 3090 (sponsored by Schneewolf Labs).

Data was prepared with Llama 3.1 Instruct.

--

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/Llama3.1-Allades-8B-Q4_K_M-GGUF --hf-file llama3.1-allades-8b-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/Llama3.1-Allades-8B-Q4_K_M-GGUF --hf-file llama3.1-allades-8b-q4_k_m.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/Llama3.1-Allades-8B-Q4_K_M-GGUF --hf-file llama3.1-allades-8b-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/Llama3.1-Allades-8B-Q4_K_M-GGUF --hf-file llama3.1-allades-8b-q4_k_m.gguf -c 2048
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Architecture
llama

4-bit

Inference API
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