Instructions to use Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit",
	filename="unsloth.F16.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit:F16
# Run inference directly in the terminal:
llama-cli -hf Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit:F16
# Run inference directly in the terminal:
llama-cli -hf Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit: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 Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit:F16
# Run inference directly in the terminal:
./llama-cli -hf Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit: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 Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit:F16

Use Docker

docker model run hf.co/Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit:F16

LM Studio
Jan

vLLM

How to use Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit:F16

Ollama
How to use Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit with Ollama:
```
ollama run hf.co/Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit:F16
```

Unsloth Studio new

How to use Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit 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 Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit 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 Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit to start chatting

Docker Model Runner
How to use Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit with Docker Model Runner:
```
docker model run hf.co/Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit:F16
```

Lemonade

How to use Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit:F16

Run and chat with the model

lemonade run user.Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit-F16

List all available models

lemonade list

Agnuxo commited on Aug 30, 2024

Commit

dec2900

verified ·

1 Parent(s): 2284cec

Update README.md

Browse files

Files changed (1) hide show

README.md +19 -6

README.md CHANGED Viewed

@@ -1,22 +1,35 @@
 ---
-base_model: unsloth/phi-3.5-mini-instruct-bnb-4bit
 language:
 - en
 license: apache-2.0
 tags:
 - text-generation-inference
 - transformers
 - unsloth
-- llama
 - gguf
 ---
 # Uploaded  model
-- **Developed by:** Agnuxo
 - **License:** apache-2.0
-- **Finetuned from model :** unsloth/phi-3.5-mini-instruct-bnb-4bit
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

 ---
+base_model: Agnuxo/Phi-3.5-mini-instruct-python_coding_assistant-GGUF_16bit
 language:
 - en
+- es
 license: apache-2.0
 tags:
 - text-generation-inference
 - transformers
 - unsloth
+- mistral
 - gguf
+datasets:
+- iamtarun/python_code_instructions_18k_alpaca
+- jtatman/python-code-dataset-500k
+- flytech/python-codes-25k
+- Vezora/Tested-143k-Python-Alpaca
+- codefuse-ai/CodeExercise-Python-27k
+- Vezora/Tested-22k-Python-Alpaca
+- mlabonne/Evol-Instruct-Python-26k
+metrics:
+- code_eval
+library_name: adapter-transformers
 ---
 # Uploaded  model
+[<img src="https://github.githubassets.com/assets/GitHub-Mark-ea2971cee799.png" width="100"/><img src="https://github.githubassets.com/assets/GitHub-Logo-ee398b662d42.png" width="100"/>](https://github.com/Agnuxo1)
+- **Developed by:** Agnuxo(https://github.com/Agnuxo1)
 - **License:** apache-2.0
+- **Finetuned from model :** Agnuxo/Mistral-NeMo-Minitron-8B-Base-Nebulal
+This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)