Nova-7B
Collection
Collection of the Nova-7B series. • 6 items • Updated • 2
How to use oscar128372/Nova-0.5-e2-7B with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="oscar128372/Nova-0.5-e2-7B")
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe(messages) # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("oscar128372/Nova-0.5-e2-7B")
model = AutoModelForCausalLM.from_pretrained("oscar128372/Nova-0.5-e2-7B")
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]:]))How to use oscar128372/Nova-0.5-e2-7B with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "oscar128372/Nova-0.5-e2-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "oscar128372/Nova-0.5-e2-7B",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker model run hf.co/oscar128372/Nova-0.5-e2-7B
How to use oscar128372/Nova-0.5-e2-7B with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "oscar128372/Nova-0.5-e2-7B" \
--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": "oscar128372/Nova-0.5-e2-7B",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'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 "oscar128372/Nova-0.5-e2-7B" \
--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": "oscar128372/Nova-0.5-e2-7B",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'How to use oscar128372/Nova-0.5-e2-7B with Unsloth Studio:
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 oscar128372/Nova-0.5-e2-7B to start chatting
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 oscar128372/Nova-0.5-e2-7B to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for oscar128372/Nova-0.5-e2-7B to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="oscar128372/Nova-0.5-e2-7B",
max_seq_length=2048,
)How to use oscar128372/Nova-0.5-e2-7B with Docker Model Runner:
docker model run hf.co/oscar128372/Nova-0.5-e2-7B
This model uses the ChatML template:
<|im_start|>system
You are a helpful assistant<|im_end|>
<|im_start|>user
What is a famous tall tower in Paris?<|im_end|>
<|im_start|>assistant
The Eiffel Tower is a famous tall tower located in Paris, France. It was designed by Gustave Eiffel and completed in 1889 for the 1889 World's Fair. The Eiffel Tower is made of wrought iron and stands at a height of 324 meters (1,063 feet). It is one of the most recognizable landmarks in the world and attracts millions of visitors each year.<|im_end|>