Instructions to use featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF",
	filename="nayohan-llama3-instrucTrans-enko-8b-IQ4_XS.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF 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 featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF: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 featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF: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 featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF:Q4_K_M

Use Docker

docker model run hf.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF:Q4_K_M

Ollama
How to use featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF with Ollama:
```
ollama run hf.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF:Q4_K_M
```

Unsloth Studio

How to use featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-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 featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-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 featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF with Docker Model Runner:
```
docker model run hf.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF:Q4_K_M
```

Lemonade

How to use featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.nayohan-llama3-instrucTrans-enko-8b-GGUF-Q4_K_M

List all available models

lemonade list

nayohan-llama3-instrucTrans-enko-8b-GGUF

File size: 3,446 Bytes

---
base_model: nayohan/llama3-instrucTrans-enko-8b
pipeline_tag: text-generation
quantized_by: featherless-ai-quants
---

# nayohan/llama3-instrucTrans-enko-8b GGUF Quantizations 🚀

![Featherless AI Quants](./featherless-quants.png)

*Optimized GGUF quantization files for enhanced model performance*

> Powered by [Featherless AI](https://featherless.ai) - run any model you'd like for a simple small fee.
---

## Available Quantizations 📊

| Quantization Type | File | Size |
|-------------------|------|------|
| IQ4_XS | [nayohan-llama3-instrucTrans-enko-8b-IQ4_XS.gguf](https://huggingface.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF/blob/main/nayohan-llama3-instrucTrans-enko-8b-IQ4_XS.gguf) | 4276.62 MB |
| Q2_K | [nayohan-llama3-instrucTrans-enko-8b-Q2_K.gguf](https://huggingface.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF/blob/main/nayohan-llama3-instrucTrans-enko-8b-Q2_K.gguf) | 3031.86 MB |
| Q3_K_L | [nayohan-llama3-instrucTrans-enko-8b-Q3_K_L.gguf](https://huggingface.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF/blob/main/nayohan-llama3-instrucTrans-enko-8b-Q3_K_L.gguf) | 4121.74 MB |
| Q3_K_M | [nayohan-llama3-instrucTrans-enko-8b-Q3_K_M.gguf](https://huggingface.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF/blob/main/nayohan-llama3-instrucTrans-enko-8b-Q3_K_M.gguf) | 3832.74 MB |
| Q3_K_S | [nayohan-llama3-instrucTrans-enko-8b-Q3_K_S.gguf](https://huggingface.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF/blob/main/nayohan-llama3-instrucTrans-enko-8b-Q3_K_S.gguf) | 3494.74 MB |
| Q4_K_M | [nayohan-llama3-instrucTrans-enko-8b-Q4_K_M.gguf](https://huggingface.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF/blob/main/nayohan-llama3-instrucTrans-enko-8b-Q4_K_M.gguf) | 4692.78 MB |
| Q4_K_S | [nayohan-llama3-instrucTrans-enko-8b-Q4_K_S.gguf](https://huggingface.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF/blob/main/nayohan-llama3-instrucTrans-enko-8b-Q4_K_S.gguf) | 4475.28 MB |
| Q5_K_M | [nayohan-llama3-instrucTrans-enko-8b-Q5_K_M.gguf](https://huggingface.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF/blob/main/nayohan-llama3-instrucTrans-enko-8b-Q5_K_M.gguf) | 5467.40 MB |
| Q5_K_S | [nayohan-llama3-instrucTrans-enko-8b-Q5_K_S.gguf](https://huggingface.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF/blob/main/nayohan-llama3-instrucTrans-enko-8b-Q5_K_S.gguf) | 5339.90 MB |
| Q6_K | [nayohan-llama3-instrucTrans-enko-8b-Q6_K.gguf](https://huggingface.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF/blob/main/nayohan-llama3-instrucTrans-enko-8b-Q6_K.gguf) | 6290.44 MB |
| Q8_0 | [nayohan-llama3-instrucTrans-enko-8b-Q8_0.gguf](https://huggingface.co/featherless-ai-quants/nayohan-llama3-instrucTrans-enko-8b-GGUF/blob/main/nayohan-llama3-instrucTrans-enko-8b-Q8_0.gguf) | 8145.11 MB |


---

## ⚡ Powered by [Featherless AI](https://featherless.ai)

### Key Features

- 🔥 **Instant Hosting** - Deploy any Llama model on HuggingFace instantly
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---

**Links:**  
[Get Started](https://featherless.ai) | [Documentation](https://featherless.ai/docs) | [Models](https://featherless.ai/models)