# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("rantidevsharma/model")
model = AutoModelForCausalLM.from_pretrained("rantidevsharma/model", device_map="auto")Quick Links
Uploaded model
- Developed by: rantidevsharma
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
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Base model
meta-llama/Meta-Llama-3-8B Quantized
unsloth/llama-3-8b-bnb-4bit
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="rantidevsharma/model")