metadata

base_model: MaziyarPanahi/calme-2.1-qwen2-7b
datasets:
  - nvidia/HelpSteer2
  - teknium/OpenHermes-2.5
  - microsoft/orca-math-word-problems-200k
  - Open-Orca/SlimOrca
language:
  - en
library_name: transformers
license: apache-2.0
model_name: calme-2.1-qwen2-7b
pipeline_tag: text-generation
tags:
  - chat
  - qwen
  - qwen2
  - finetune
  - chatml
  - OpenHermes-2.5
  - HelpSteer2
  - Orca
  - SlimOrca
  - llama-cpp
  - gguf-my-repo
inference: false
model_creator: MaziyarPanahi
quantized_by: MaziyarPanahi

hellork/calme-2.1-qwen2-7b-IQ4_NL-GGUF

This model was converted to GGUF format from MaziyarPanahi/calme-2.1-qwen2-7b using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

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 hellork/calme-2.1-qwen2-7b-IQ4_NL-GGUF --hf-file calme-2.1-qwen2-7b-iq4_nl-imat.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo hellork/calme-2.1-qwen2-7b-IQ4_NL-GGUF --hf-file calme-2.1-qwen2-7b-iq4_nl-imat.gguf -c 2048

The Ship's Computer:

Interact with this model by speaking to it. Lean, fast, & private, networked speech to text, AI images, multi-modal voice chat, control apps, webcam, and sound with less than 4GiB of VRAM. whisper_dictation

Quick start

git clone -b main --single-branch https://github.com/themanyone/whisper_dictation.git
pip install -r whisper_dictation/requirements.txt

git clone https://github.com/ggerganov/whisper.cpp
cd whisper.cpp
GGML_CUDA=1 make -j # assuming CUDA is available. see docs
ln -s server ~/.local/bin/whisper_cpp_server # (just put it somewhere in $PATH)
whisper_cpp_server -l en -m models/ggml-tiny.en.bin --port 7777

# -ngl option assumes CUDA is available. see docs
llama-server --hf-repo hellork/calme-2.1-qwen2-7b-IQ4_NL-GGUF --hf-file calme-2.1-qwen2-7b-iq4_nl-imat.gguf -c 2048 -ngl 17 --port 8888

cd whisper_dictation
./whisper_cpp_client.py

See the docs for tips on enabling the computer to talk back, draw AI images, carry out voice commands, and other features.

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 hellork/calme-2.1-qwen2-7b-IQ4_NL-GGUF --hf-file calme-2.1-qwen2-7b-iq4_nl-imat.gguf -p "The meaning to life and the universe is"

./llama-server --hf-repo hellork/calme-2.1-qwen2-7b-IQ4_NL-GGUF --hf-file calme-2.1-qwen2-7b-iq4_nl-imat.gguf -c 2048