Instructions to use Jay1121/blossom_7B_final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Jay1121/blossom_7B_final with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Jay1121/blossom_7B_final", filename="qwen2.5-7b-instruct.Q4_K_M.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Jay1121/blossom_7B_final with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Jay1121/blossom_7B_final:Q4_K_M # Run inference directly in the terminal: llama cli -hf Jay1121/blossom_7B_final:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Jay1121/blossom_7B_final:Q4_K_M # Run inference directly in the terminal: llama cli -hf Jay1121/blossom_7B_final:Q4_K_M
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 Jay1121/blossom_7B_final:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Jay1121/blossom_7B_final:Q4_K_M
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 Jay1121/blossom_7B_final:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Jay1121/blossom_7B_final:Q4_K_M
Use Docker
docker model run hf.co/Jay1121/blossom_7B_final:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Jay1121/blossom_7B_final with Ollama:
ollama run hf.co/Jay1121/blossom_7B_final:Q4_K_M
- Unsloth Studio
How to use Jay1121/blossom_7B_final 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 Jay1121/blossom_7B_final 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 Jay1121/blossom_7B_final to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Jay1121/blossom_7B_final to start chatting
- Atomic Chat new
- Docker Model Runner
How to use Jay1121/blossom_7B_final with Docker Model Runner:
docker model run hf.co/Jay1121/blossom_7B_final:Q4_K_M
- Lemonade
How to use Jay1121/blossom_7B_final with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Jay1121/blossom_7B_final:Q4_K_M
Run and chat with the model
lemonade run user.blossom_7B_final-Q4_K_M
List all available models
lemonade list
Upload GGUF Q4_K_M quantized model
Browse filesFine-tuned Qwen2.5-7B-Instruct with Korean conversational data
- .gitattributes +1 -0
- qwen2.5-7b-instruct.Q4_K_M.gguf +3 -0
.gitattributes
CHANGED
|
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
qwen2.5-7b-instruct.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
|
qwen2.5-7b-instruct.Q4_K_M.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:71fe3ab5ce47e49216075468422b703a5db537b4308bcd423ae9182b0a50a2b6
|
| 3 |
+
size 4683071776
|