Instructions to use nectec/Pathumma-llm-text-1.0.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nectec/Pathumma-llm-text-1.0.0 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="nectec/Pathumma-llm-text-1.0.0",
	filename="Pathumma-llm-it-7b-Q4_K_M.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 nectec/Pathumma-llm-text-1.0.0 with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf nectec/Pathumma-llm-text-1.0.0:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf nectec/Pathumma-llm-text-1.0.0:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf nectec/Pathumma-llm-text-1.0.0:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf nectec/Pathumma-llm-text-1.0.0: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 nectec/Pathumma-llm-text-1.0.0:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf nectec/Pathumma-llm-text-1.0.0: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 nectec/Pathumma-llm-text-1.0.0:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf nectec/Pathumma-llm-text-1.0.0:Q4_K_M

Use Docker

docker model run hf.co/nectec/Pathumma-llm-text-1.0.0:Q4_K_M

LM Studio
Jan

vLLM

How to use nectec/Pathumma-llm-text-1.0.0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nectec/Pathumma-llm-text-1.0.0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nectec/Pathumma-llm-text-1.0.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/nectec/Pathumma-llm-text-1.0.0:Q4_K_M

Ollama
How to use nectec/Pathumma-llm-text-1.0.0 with Ollama:
```
ollama run hf.co/nectec/Pathumma-llm-text-1.0.0:Q4_K_M
```

Unsloth Studio new

How to use nectec/Pathumma-llm-text-1.0.0 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 nectec/Pathumma-llm-text-1.0.0 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 nectec/Pathumma-llm-text-1.0.0 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for nectec/Pathumma-llm-text-1.0.0 to start chatting

Pi new

How to use nectec/Pathumma-llm-text-1.0.0 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf nectec/Pathumma-llm-text-1.0.0:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "nectec/Pathumma-llm-text-1.0.0:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use nectec/Pathumma-llm-text-1.0.0 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf nectec/Pathumma-llm-text-1.0.0:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default nectec/Pathumma-llm-text-1.0.0:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use nectec/Pathumma-llm-text-1.0.0 with Docker Model Runner:
```
docker model run hf.co/nectec/Pathumma-llm-text-1.0.0:Q4_K_M
```

Lemonade

How to use nectec/Pathumma-llm-text-1.0.0 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull nectec/Pathumma-llm-text-1.0.0:Q4_K_M

Run and chat with the model

lemonade run user.Pathumma-llm-text-1.0.0-Q4_K_M

List all available models

lemonade list

Pakawat Phasook commited on Oct 24, 2024

Commit

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@@ -77,11 +77,11 @@ print(response)
 ## **Evaluation Performance**
 | Model | m3exam | thaiexam | xcopa | belebele | xnli | thaisentiment | XL sum | flores200 eng > th | flores200 th > eng | iapp | AVG(NLU) | AVG(MC) | AVG(NLG) |
 | :--- | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
-| Pathumma-llm-text-1.0.0 | 55.02 | 51.32 | 83 | 77.77 | 40.11 | 41.29 | 16.9286253 | 26.54 | 51.88 | 41.28 | 60.54 | 53.17 | 34.16 |
-| Openthaigpt1.5-7b-instruct | 54.01 | 52.04 | 85.4 | 79.44 | 39.7 | 50.24 | 18.11 | 29.09 | 29.58 | 32.49 | 63.70 | 53.03 | 27.32 |
-| SeaLLMs-v3-7B-Chat | 51.43 | 51.33 | 83.4 | 78.22 | 34.05 | 39.57 | 20.27 | 32.91 | 28.8 | 48.12 | 58.81 | 51.38 | 32.53 |
 | llama-3-typhoon-v1.5-8B | 43.82 | 41.95 | 81.6 | 71.89 | 33.35 | 38.45 | 16.66 | 31.94 | 28.86 | 54.78 | 56.32 | 42.89 | 33.06 |
-| Meta-Llama-3.1-8B-Instruct | 45.11 | 43.89 | 73.4 | 74.89 | 33.49 | 45.45 | 21.61 | 30.45 | 32.28 | 68.57 | 56.81 | 44.50 | 38.23 |
 ## **Contributor Contract**

 ## **Evaluation Performance**
 | Model | m3exam | thaiexam | xcopa | belebele | xnli | thaisentiment | XL sum | flores200 eng > th | flores200 th > eng | iapp | AVG(NLU) | AVG(MC) | AVG(NLG) |
 | :--- | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
+| Pathumma-llm-text-1.0.0 | **55.02** | 51.32 | 83 | 77.77 | **40.11** | 41.29 | 16.9286253 | 26.54 | **51.88** | 41.28 | 60.54 | **53.17** | 34.16 |
+| Openthaigpt1.5-7b-instruct | 54.01 | **52.04** | **85.4** | **79.44** | 39.7 | **50.24** | 18.11 | 29.09 | 29.58 | 32.49 | **63.70** | 53.03 | 27.32 |
+| SeaLLMs-v3-7B-Chat | 51.43 | 51.33 | 83.4 | 78.22 | 34.05 | 39.57 | 20.27 | **32.91** | 28.8 | 48.12 | 58.81 | 51.38 | 32.53 |
 | llama-3-typhoon-v1.5-8B | 43.82 | 41.95 | 81.6 | 71.89 | 33.35 | 38.45 | 16.66 | 31.94 | 28.86 | 54.78 | 56.32 | 42.89 | 33.06 |
+| Meta-Llama-3.1-8B-Instruct | 45.11 | 43.89 | 73.4 | 74.89 | 33.49 | 45.45 | **21.61** | 30.45 | 32.28 | **68.57** | 56.81 | 44.50 | **38.23** |
 ## **Contributor Contract**