Instructions to use pdjohn/Llama-3-TRACHI-8B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use pdjohn/Llama-3-TRACHI-8B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="pdjohn/Llama-3-TRACHI-8B-Instruct")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("pdjohn/Llama-3-TRACHI-8B-Instruct")
model = AutoModelForCausalLM.from_pretrained("pdjohn/Llama-3-TRACHI-8B-Instruct")
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use pdjohn/Llama-3-TRACHI-8B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "pdjohn/Llama-3-TRACHI-8B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "pdjohn/Llama-3-TRACHI-8B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/pdjohn/Llama-3-TRACHI-8B-Instruct

SGLang

How to use pdjohn/Llama-3-TRACHI-8B-Instruct 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 "pdjohn/Llama-3-TRACHI-8B-Instruct" \
    --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": "pdjohn/Llama-3-TRACHI-8B-Instruct",
		"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 "pdjohn/Llama-3-TRACHI-8B-Instruct" \
        --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": "pdjohn/Llama-3-TRACHI-8B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use pdjohn/Llama-3-TRACHI-8B-Instruct with Docker Model Runner:
```
docker model run hf.co/pdjohn/Llama-3-TRACHI-8B-Instruct
```

Llama-3-TRACHI-8B-Instruct

Commit History

Update README.md

f1b6261
verified

Patrick Johnson commited on Jul 27, 2025

Update README.md

6d1d420
verified

Patrick Johnson commited on Jul 27, 2025

Upload tokenizer

93ec751
verified

Patrick Johnson commited on Apr 24, 2024

Upload LlamaForCausalLM

a58296a
verified

Patrick Johnson commited on Apr 24, 2024

initial commit

7c565ab
verified

Patrick Johnson commited on Apr 24, 2024

Commit History

Update README.md f1b6261 verified

Update README.md 6d1d420 verified

Upload tokenizer 93ec751 verified

Upload LlamaForCausalLM a58296a verified

initial commit 7c565ab verified

Update README.md

f1b6261
verified

Update README.md

6d1d420
verified

Upload tokenizer

93ec751
verified

Upload LlamaForCausalLM

a58296a
verified

initial commit

7c565ab
verified