Instructions to use Tamnemtf/llama-2-7b-vi-oscar_mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Tamnemtf/llama-2-7b-vi-oscar_mini with Transformers:

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

pipe = pipeline("text-generation", model="Tamnemtf/llama-2-7b-vi-oscar_mini")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Tamnemtf/llama-2-7b-vi-oscar_mini")
model = AutoModelForCausalLM.from_pretrained("Tamnemtf/llama-2-7b-vi-oscar_mini", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Tamnemtf/llama-2-7b-vi-oscar_mini with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Tamnemtf/llama-2-7b-vi-oscar_mini"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Tamnemtf/llama-2-7b-vi-oscar_mini",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Tamnemtf/llama-2-7b-vi-oscar_mini

SGLang

How to use Tamnemtf/llama-2-7b-vi-oscar_mini 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 "Tamnemtf/llama-2-7b-vi-oscar_mini" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Tamnemtf/llama-2-7b-vi-oscar_mini",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "Tamnemtf/llama-2-7b-vi-oscar_mini" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Tamnemtf/llama-2-7b-vi-oscar_mini",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Tamnemtf/llama-2-7b-vi-oscar_mini with Docker Model Runner:
```
docker model run hf.co/Tamnemtf/llama-2-7b-vi-oscar_mini
```

Model Details

Model Name: llama-2-7b-vi-oscar_mini
Purpose: Mục đích để train con model này để phục vụ việc học và đề tài nckh.
Availability: The model checkpoint can be accessed on Hugging Face: Tamnemtf/llama-2-7b-vi-oscar_mini
Model trên được train dựa trên model gốc là ngoan/Llama-2-7b-vietnamese-20k

How to Use

  # Run text generation pipeline with our next model
  prompt = "Canh chua cá lau là món gì ?"
  pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=200)
  result = pipe(f"<s>[INST] {prompt} [/INST]")
  print(result[0]['generated_text'])

Conntact

nguyndantdm6@gmail.com

Downloads last month: 4

Safetensors

Model size

7B params

Tensor type

F16

Model tree for Tamnemtf/llama-2-7b-vi-oscar_mini

Base model

ngoan/Llama-2-7b-vietnamese-20k

Finetuned

(1)

this model

Tamnemtf
/

llama-2-7b-vi-oscar_mini

Model Details

How to Use

Conntact

Model tree for Tamnemtf/llama-2-7b-vi-oscar_mini

Datasets used to train Tamnemtf/llama-2-7b-vi-oscar_mini