Russian speaking 7B models
Collection
There is some my 7B models good speak and understand Russian language. Approved by some data-set my own tests. Will be link to github repo soon...🪬 • 7 items • Updated • 3
How to use AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf", filename="KSI-RP-NSK-128k-7B.q2_k.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
How to use AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf with llama.cpp:
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf:Q4_K_M # Run inference directly in the terminal: llama-cli -hf AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf:Q4_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf:Q4_K_M # Run inference directly in the terminal: llama-cli -hf AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf:Q4_K_M
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf:Q4_K_M
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf:Q4_K_M
docker model run hf.co/AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf:Q4_K_M
How to use AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf with Ollama:
ollama run hf.co/AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf:Q4_K_M
How to use AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf to start chatting
How to use AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf with Docker Model Runner:
docker model run hf.co/AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf:Q4_K_M
How to use AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull AlekseiPravdin/KSI-RP-NSK-128k-7B-gguf:Q4_K_M
lemonade run user.KSI-RP-NSK-128k-7B-gguf-Q4_K_M
lemonade list
KSI-RP-NSK-128k-7B is a merge of the following models using mergekit:
slices:
- sources:
- model: AlekseiPravdin/KukulStanta-InfinityRP-7B-slerp
layer_range: [0, 32]
- model: AlekseiPravdin/NSK-128k-7B-slerp
layer_range: [0, 32]
merge_method: slerp
base_model: AlekseiPravdin/NSK-128k-7B-slerp
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
Eval embedding benchmark (with 70 specific quesions):
2-bit
3-bit
4-bit
5-bit
6-bit
8-bit