Instructions to use herMaster/Llama2-7b-Finance-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use herMaster/Llama2-7b-Finance-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="herMaster/Llama2-7b-Finance-GGUF")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("herMaster/Llama2-7b-Finance-GGUF") model = AutoModelForCausalLM.from_pretrained("herMaster/Llama2-7b-Finance-GGUF") - llama-cpp-python
How to use herMaster/Llama2-7b-Finance-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="herMaster/Llama2-7b-Finance-GGUF", filename="Llama2-7b-Finance-f16.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use herMaster/Llama2-7b-Finance-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf herMaster/Llama2-7b-Finance-GGUF:F16 # Run inference directly in the terminal: llama-cli -hf herMaster/Llama2-7b-Finance-GGUF:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf herMaster/Llama2-7b-Finance-GGUF:F16 # Run inference directly in the terminal: llama-cli -hf herMaster/Llama2-7b-Finance-GGUF:F16
Use pre-built binary
# 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 herMaster/Llama2-7b-Finance-GGUF:F16 # Run inference directly in the terminal: ./llama-cli -hf herMaster/Llama2-7b-Finance-GGUF:F16
Build from source code
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 herMaster/Llama2-7b-Finance-GGUF:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf herMaster/Llama2-7b-Finance-GGUF:F16
Use Docker
docker model run hf.co/herMaster/Llama2-7b-Finance-GGUF:F16
- LM Studio
- Jan
- vLLM
How to use herMaster/Llama2-7b-Finance-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "herMaster/Llama2-7b-Finance-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "herMaster/Llama2-7b-Finance-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/herMaster/Llama2-7b-Finance-GGUF:F16
- SGLang
How to use herMaster/Llama2-7b-Finance-GGUF with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "herMaster/Llama2-7b-Finance-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "herMaster/Llama2-7b-Finance-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "herMaster/Llama2-7b-Finance-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "herMaster/Llama2-7b-Finance-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Ollama
How to use herMaster/Llama2-7b-Finance-GGUF with Ollama:
ollama run hf.co/herMaster/Llama2-7b-Finance-GGUF:F16
- Unsloth Studio new
How to use herMaster/Llama2-7b-Finance-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
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 herMaster/Llama2-7b-Finance-GGUF to start chatting
Install Unsloth Studio (Windows)
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 herMaster/Llama2-7b-Finance-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for herMaster/Llama2-7b-Finance-GGUF to start chatting
- Docker Model Runner
How to use herMaster/Llama2-7b-Finance-GGUF with Docker Model Runner:
docker model run hf.co/herMaster/Llama2-7b-Finance-GGUF:F16
- Lemonade
How to use herMaster/Llama2-7b-Finance-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull herMaster/Llama2-7b-Finance-GGUF:F16
Run and chat with the model
lemonade run user.Llama2-7b-Finance-GGUF-F16
List all available models
lemonade list
Llama2 7b Finance f16 - GGUF
- Model creator: Meta Llama 2
- Original model: Llama2-7b-Finance
Model Description
This repo contains GGUF format model files for cxllin's Llama 2 7b Finance.
About GGUF
GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. GGUF offers numerous advantages over GGML, such as better tokenisation, and support for special tokens. It is also supports metadata, and is designed to be extensible.
Here is an incomplate list of clients and libraries that are known to support GGUF:
- llama.cpp. The source project for GGUF. Offers a CLI and a server option.
- text-generation-webui, the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
- KoboldCpp, a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
- LM Studio, an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration.
- LoLLMS Web UI, a great web UI with many interesting and unique features, including a full model library for easy model selection.
- Faraday.dev, an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration.
- ctransformers, a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server.
- llama-cpp-python, a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
- candle, a Rust ML framework with a focus on performance, including GPU support, and ease of use.
Repositories available
- AWQ model(s) for GPU inference.
- GPTQ models for GPU inference, with multiple quantisation parameter options.
- 2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference
- Meta Llama 2's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions
Prompt template: Llama-2-Chat
[INST] <<SYS>>
You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.
<</SYS>>
{prompt}[/INST]
Compatibility
These quantised GGUFv2 files are compatible with llama.cpp from August 27th onwards, as of commit d0cee0d36d5be95a0d9088b674dbb27354107221
They are also compatible with many third-party UIs and libraries - please see the list at the top of this README.
- Developed by: [devpagare002@gmail.com]
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Model tree for herMaster/Llama2-7b-Finance-GGUF
Base model
cxllin/Llama2-7b-Finance