ResplendentAI/Synthetic_Soul_1k
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How to use bartowski/Flora_7B-GGUF with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="bartowski/Flora_7B-GGUF") # Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("bartowski/Flora_7B-GGUF", device_map="auto")How to use bartowski/Flora_7B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="bartowski/Flora_7B-GGUF", filename="Flora_7B-Q2_K.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
How to use bartowski/Flora_7B-GGUF with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf bartowski/Flora_7B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf bartowski/Flora_7B-GGUF:Q4_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf bartowski/Flora_7B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf bartowski/Flora_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 bartowski/Flora_7B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf bartowski/Flora_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 bartowski/Flora_7B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf bartowski/Flora_7B-GGUF:Q4_K_M
docker model run hf.co/bartowski/Flora_7B-GGUF:Q4_K_M
How to use bartowski/Flora_7B-GGUF with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bartowski/Flora_7B-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "bartowski/Flora_7B-GGUF",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/bartowski/Flora_7B-GGUF:Q4_K_M
How to use bartowski/Flora_7B-GGUF with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "bartowski/Flora_7B-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": "bartowski/Flora_7B-GGUF",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'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 "bartowski/Flora_7B-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": "bartowski/Flora_7B-GGUF",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'How to use bartowski/Flora_7B-GGUF with Ollama:
ollama run hf.co/bartowski/Flora_7B-GGUF:Q4_K_M
How to use bartowski/Flora_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 bartowski/Flora_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 bartowski/Flora_7B-GGUF to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for bartowski/Flora_7B-GGUF to start chatting
How to use bartowski/Flora_7B-GGUF with Docker Model Runner:
docker model run hf.co/bartowski/Flora_7B-GGUF:Q4_K_M
How to use bartowski/Flora_7B-GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bartowski/Flora_7B-GGUF:Q4_K_M
lemonade run user.Flora_7B-GGUF-Q4_K_M
lemonade list
Using llama.cpp release b2334 for quantization.
Original model: https://huggingface.co/ResplendentAI/Flora_7B
Download a file (not the whole branch) from below:
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| Flora_7B-Q8_0.gguf | Q8_0 | 7.69GB | Extremely high quality, generally unneeded but max available quant. |
| Flora_7B-Q6_K.gguf | Q6_K | 5.94GB | Very high quality, near perfect, recommended. |
| Flora_7B-Q5_K_M.gguf | Q5_K_M | 5.13GB | High quality, very usable. |
| Flora_7B-Q5_K_S.gguf | Q5_K_S | 4.99GB | High quality, very usable. |
| Flora_7B-Q5_0.gguf | Q5_0 | 4.99GB | High quality, older format, generally not recommended. |
| Flora_7B-Q4_K_M.gguf | Q4_K_M | 4.36GB | Good quality, similar to 4.25 bpw. |
| Flora_7B-Q4_K_S.gguf | Q4_K_S | 4.14GB | Slightly lower quality with small space savings. |
| Flora_7B-Q4_0.gguf | Q4_0 | 4.10GB | Decent quality, older format, generally not recommended. |
| Flora_7B-Q3_K_L.gguf | Q3_K_L | 3.82GB | Lower quality but usable, good for low RAM availability. |
| Flora_7B-Q3_K_M.gguf | Q3_K_M | 3.51GB | Even lower quality. |
| Flora_7B-Q3_K_S.gguf | Q3_K_S | 3.16GB | Low quality, not recommended. |
| Flora_7B-Q2_K.gguf | Q2_K | 2.71GB | Extremely low quality, not recommended. |
Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski
Base model
jeiku/FloraBase