Duplicated from EliasAhl/llama-3-8b-Instruct-cefr-tuned-v2
How to use orionbits/llama-3-8b-Instruct-cefr-tuned-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="orionbits/llama-3-8b-Instruct-cefr-tuned-v2")
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("orionbits/llama-3-8b-Instruct-cefr-tuned-v2") model = AutoModelForCausalLM.from_pretrained("orionbits/llama-3-8b-Instruct-cefr-tuned-v2", device_map="auto")
How to use orionbits/llama-3-8b-Instruct-cefr-tuned-v2 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 orionbits/llama-3-8b-Instruct-cefr-tuned-v2 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 orionbits/llama-3-8b-Instruct-cefr-tuned-v2 to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for orionbits/llama-3-8b-Instruct-cefr-tuned-v2 to start chatting
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="orionbits/llama-3-8b-Instruct-cefr-tuned-v2", max_seq_length=2048, )
