base_model: stephenlzc/Mistral-7B-v0.3-Chinese-Chat-uncensored
datasets:
- Minami-su/toxic-sft-zh
- llm-wizard/alpaca-gpt4-data-zh
- stephenlzc/stf-alpaca
language: - zh
license: mit
pipeline_tag: text-generation
tags: - text-generation-inference
- code
- unsloth
- uncensored
- finetune
- llama-cpp
- gguf-my-repo
task_categories: - conversational
widget: - text: 'Is this review positive or negative? Review: Best cast iron skillet you will
ever buy.'
example_title: Sentiment analysis - text: Barack Obama nominated Hilary Clinton as his secretary of state on Monday.
He chose her because she had ...
example_title: Coreference resolution - text: 'On a shelf, there are five books: a gray book, a red book, a purple book,
a blue book, and a black book ...'
example_title: Logic puzzles - text: The two men running to become New York City's next mayor will face off in
their first debate Wednesday night ...
example_title: Reading comprehension
fengpeisheng1/Mistral-7B-v0.3-Chinese-Chat-uncensored-IQ4_NL-GGUF
This model was converted to GGUF format from stephenlzc/Mistral-7B-v0.3-Chinese-Chat-uncensored 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 fengpeisheng1/Mistral-7B-v0.3-Chinese-Chat-uncensored-IQ4_NL-GGUF --hf-file mistral-7b-v0.3-chinese-chat-uncensored-iq4_nl-imat.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo fengpeisheng1/Mistral-7B-v0.3-Chinese-Chat-uncensored-IQ4_NL-GGUF --hf-file mistral-7b-v0.3-chinese-chat-uncensored-iq4_nl-imat.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 fengpeisheng1/Mistral-7B-v0.3-Chinese-Chat-uncensored-IQ4_NL-GGUF --hf-file mistral-7b-v0.3-chinese-chat-uncensored-iq4_nl-imat.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo fengpeisheng1/Mistral-7B-v0.3-Chinese-Chat-uncensored-IQ4_NL-GGUF --hf-file mistral-7b-v0.3-chinese-chat-uncensored-iq4_nl-imat.gguf -c 2048