π HelpingAI-Lite-1.5T Model Card π
π Datasets used:
- cerebras/SlimPajama-627B
- HuggingFaceH4/ultrachat_200k
- bigcode/starcoderdata
- HuggingFaceH4/ultrafeedback_binarized
- OEvortex/vortex-mini
- Open-Orca/OpenOrca
π£οΈ Language:
- English (en)
π License:
HelpingAI Simplified Universal License (HSUL)
π§ Model Overview: HelpingAI-Lite-1.5T is an advanced version of the HelpingAI-Lite model, trained on a vast corpus of 1.5 trillion tokens. This extensive training data enables the model to provide precise and insightful responses, particularly for coding tasks.
π§ Usage Example:
from transformers import pipeline
from accelerate import Accelerator
# Initialize the accelerator
accelerator = Accelerator()
# Initialize the pipeline
pipe = pipeline("text-generation", model="OEvortex/HelpingAI-Lite-1.5T", device=accelerator.device)
# Define the messages
messages = [
{
"role": "system",
"content": "You are a chatbot who can be a teacher",
},
{
"role": "user",
"content": "Explain me working of AI.",
},
]
# Prepare the prompt
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
# Generate predictions
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
# Print the generated text
print(outputs[0]["generated_text"])
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