Instructions to use traeval/tesla1500_llama2_7b-2-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use traeval/tesla1500_llama2_7b-2-7b with Transformers:

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

pipe = pipeline("text-generation", model="traeval/tesla1500_llama2_7b-2-7b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("traeval/tesla1500_llama2_7b-2-7b")
model = AutoModelForCausalLM.from_pretrained("traeval/tesla1500_llama2_7b-2-7b")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use traeval/tesla1500_llama2_7b-2-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "traeval/tesla1500_llama2_7b-2-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "traeval/tesla1500_llama2_7b-2-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/traeval/tesla1500_llama2_7b-2-7b

SGLang

How to use traeval/tesla1500_llama2_7b-2-7b 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 "traeval/tesla1500_llama2_7b-2-7b" \
    --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": "traeval/tesla1500_llama2_7b-2-7b",
		"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 "traeval/tesla1500_llama2_7b-2-7b" \
        --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": "traeval/tesla1500_llama2_7b-2-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use traeval/tesla1500_llama2_7b-2-7b with Docker Model Runner:
```
docker model run hf.co/traeval/tesla1500_llama2_7b-2-7b
```

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

***** train metrics ***** epoch = 1.33 total_flos = 14124142GF train_loss = 0.7836 train_runtime = 1:27:16.97 train_samples_per_second = 0.382 train_steps_per_second = 0.095 {'train_runtime': 5236.9755, 'train_samples_per_second': 0.382, 'train_steps_per_second': 0.095, 'total_flos': 1.5165682398461952e+16, 'train_loss': 0.7835705888271332, 'epoch': 1.33}

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