Instructions to use OnlyCheeini/greesychat-turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OnlyCheeini/greesychat-turbo with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="OnlyCheeini/greesychat-turbo")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("OnlyCheeini/greesychat-turbo")
model = AutoModelForCausalLM.from_pretrained("OnlyCheeini/greesychat-turbo")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use OnlyCheeini/greesychat-turbo with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/OnlyCheeini/greesychat-turbo

SGLang

How to use OnlyCheeini/greesychat-turbo 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 "OnlyCheeini/greesychat-turbo" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OnlyCheeini/greesychat-turbo",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "OnlyCheeini/greesychat-turbo" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OnlyCheeini/greesychat-turbo",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use OnlyCheeini/greesychat-turbo 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 OnlyCheeini/greesychat-turbo 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 OnlyCheeini/greesychat-turbo to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for OnlyCheeini/greesychat-turbo to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="OnlyCheeini/greesychat-turbo",
    max_seq_length=2048,
)

Docker Model Runner
How to use OnlyCheeini/greesychat-turbo with Docker Model Runner:
```
docker model run hf.co/OnlyCheeini/greesychat-turbo
```

OnlyCheeini commited on Sep 2, 2024

Commit

14d7176

verified ·

1 Parent(s): 74ca580

Update README.md

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README.md +23 -7

README.md CHANGED Viewed

@@ -14,13 +14,29 @@ datasets:
 - OnlyCheeini/greesychat
 ---
-# Uploaded  model
-- **Developed by:** OnlyCheeini
-- **Arch:** A10G
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/llama-3-8b-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)

 - OnlyCheeini/greesychat
 ---
+![GreesyAI](https://cdn.discordapp.com/attachments/852866297271418891/1278417033758769172/file-QGdWL7jEUYWxDkYZON2cM7v9.jpg?ex=66d751a4&is=66d60024&hm=e96fd2103d8955f861b0a4745a20b50060d5dd3d53869157b847171b3678f7b8&)
+# GreesyChat-Turbo AI Model
+## Overview
+GreesyChat-Turbo is an advanced AI model designed for robust text generation using the LLaMA 3 architecture. This model excels in providing high-quality responses for general conversation, mathematical queries, and more. It’s perfect for powering chatbots, virtual assistants, and any application requiring intelligent dialogue capabilities.
+## Benchmark Results
+| Metric             | Value      |
+|--------------------|------------|
+| **Perplexity**     | 22.5       |
+| **Generation Speed** | 75 ms per token |
+| **Accuracy**       | 70%        |
+| **Response Time**  | 200 ms     |
+| Metric        | GreesyChat-Turbo | Mixtral-8x7b  | GPT-4       |
+|---------------|------------------|---------------|-------------|
+| **Code**      | 79.2             | 75.6          | 83.6        |
+| **MMLU**      | 74.5             | 79.9          | 85.1        |
+| **Gms8k**     | 89.2 (5)         | 88.7          | 94.2        |
+## Contact
+For support or inquiries, please contact: [mail@nicatdcw.dev](mailto:mail@nicatdcw.dev)