How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Striker-7/finetuned"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Striker-7/finetuned",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker
docker model run hf.co/Striker-7/finetuned
Quick Links

finetuned

finetuned is an SFT fine-tuned version of EleutherAI/gpt-neo-2.7B using a custom training dataset. This model was made with Phinetune

Process

  • Learning Rate: 0.0001
  • Maximum Sequence Length: 2048
  • Dataset: Striker-7/mattxt
  • Split: train

馃捇 Usage

!pip install -qU transformers
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model = "Striker-7/finetuned"
tokenizer = AutoTokenizer.from_pretrained(model)

# Example prompt
prompt = "Your example prompt here"

# Generate a response
model = AutoModelForCausalLM.from_pretrained(model)
pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
outputs = pipeline(prompt, max_length=50, num_return_sequences=1)
print(outputs[0]["generated_text"])
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Model size
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Tensor type
F32
BF16
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