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

Update README.md

by Pakawat-Phasook - opened Oct 24, 2024

base: refs/heads/main

←

from: refs/pr/3

Discussion Files changed

-6

Files changed (1) hide show

README.md +4 -6

README.md CHANGED Viewed

@@ -18,14 +18,12 @@ tags:
 - medical
 - text-generation-inference
 ---
-# **OpenThaiLLM-Prebuilt-7B: Thai & China & English Large Language Model**
-**OpenThaiLLM-Prebuilt-7B** is a Thai 🇹🇭 & Chinese 🇨🇳 large language model with 7 billion parameters, and it is continue pretrain based on Qwen2-7B.
-It demonstrates competitive performance with llama-3-typhoon-v1.5-8b, and is optimized for application use cases, Retrieval-Augmented Generation (RAG),
 constrained generation, and reasoning tasks.
-For release notes, please see our [blog](https://medium.com/@superkingbasskb/openthaillm-prebuilt-release-f1b0e22be6a5).
-**We do not recommend using base language models for conversations.** Instead, you can apply post-training, e.g., SFT, RLHF, continued pretraining, etc., on this model.
 ## **Requirements**
 The code of Qwen2.5 has been in the latest Hugging face `transformers` and we advise you to use the latest version of `transformers`.

 - medical
 - text-generation-inference
 ---
+# **PathummaLLM-text-1.0.0-7B: Thai & China & English Large Language Model Instruct**
+**PathummaLLM-text-1.0.0-7B** is a Thai 🇹🇭 & Chinese 🇨🇳 large language model with 7 billion parameters, and it is Instruction finetune based on OpenThaiLLM-Prebuilt.
+It demonstrates competitive performance with Openthaigpt1.5-7b-instruct, and its optimized for application use cases, Retrieval-Augmented Generation (RAG),
 constrained generation, and reasoning tasks.
+For release notes, please see our [blog](https://medium.com/@superkingbasskb/pathummallm-text-v-1-0-0-release-f404ff40905a).
 ## **Requirements**
 The code of Qwen2.5 has been in the latest Hugging face `transformers` and we advise you to use the latest version of `transformers`.