Text Generation
Transformers
PyTorch
llama
text-generation-inference
How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ataberkd/llama-2-13b-SQL_FINETUNED_1K"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ataberkd/llama-2-13b-SQL_FINETUNED_1K",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker
docker model run hf.co/ataberkd/llama-2-13b-SQL_FINETUNED_1K
Quick Links

πŸ’» Usage

!pip install -q accelerate==0.21.0 transformers==4.31.0

import os
import torch
from transformers import (
    AutoModelForCausalLM,
    AutoTokenizer,
    pipeline,
    logging,
)

model = "ataberkd/llama-2-13b-SQL_FINETUNED_1K"
prompt = 'You are an expert in SQL and data analysis. Given the table structure described by the CREATE TABLE statement, write an SQL query that provides the solution to the question and give the explanation of result your giving. CREATE TABLE statement: CREATE TABLE "user" ( "name" text, "surname" text, "tel" text, "address" text, "performanceScore" text,"Age" text, "Language" text );. Question: "Can you bring users who speak French and are greater than 20 years old?"'

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

sequences = pipeline(
    f'<s>[INST] {prompt} [/INST]',
    do_sample=True,
    top_k=10,
    num_return_sequences=1,
    eos_token_id=tokenizer.eos_token_id,
    max_length=200,
)
for seq in sequences:
    print(f"Result: {seq['generated_text']}")
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Dataset used to train ataberkd/llama-2-13b-SQL_FINETUNED_1K