output = llm(
"Once upon a time,",
max_tokens=512,
echo=True
)
print(output)hellork/finance-chat-IQ4_NL-GGUF
This model was converted to GGUF format from AdaptLLM/finance-chat 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/finance-chat-IQ4_NL-GGUF --hf-file finance-chat-iq4_nl-imat.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo hellork/finance-chat-IQ4_NL-GGUF --hf-file finance-chat-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 or othr AI acceleration is available. see docs
llama-server --hf-repo hellork/finance-chat-IQ4_NL-GGUF --hf-file finance-chat-iq4_nl-imat.gguf -c 2048 -ngl 17 --port 8888
cd whisper_dictation
./whisper_cpp_client.py
Install llama.cpp via git:
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/finance-chat-IQ4_NL-GGUF --hf-file finance-chat-iq4_nl-imat.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo hellork/finance-chat-IQ4_NL-GGUF --hf-file finance-chat-iq4_nl-imat.gguf -c 2048
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Base model
AdaptLLM/finance-chatDatasets used to train hellork/finance-chat-IQ4_NL-GGUF
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard53.750
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard76.600
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard50.160
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard44.540
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard75.690
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard18.800
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="hellork/finance-chat-IQ4_NL-GGUF", filename="finance-chat-iq4_nl-imat.gguf", )