Text Classification
Transformers
PyTorch
English
llama
text-generation
llama-2
text-embeddings-inference
Instructions to use Mikael110/llama-2-7b-guanaco-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mikael110/llama-2-7b-guanaco-fp16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mikael110/llama-2-7b-guanaco-fp16")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Mikael110/llama-2-7b-guanaco-fp16") model = AutoModelForCausalLM.from_pretrained("Mikael110/llama-2-7b-guanaco-fp16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
This is a Llama-2 version of Guanaco. It was finetuned from the base Llama-7b model using the official training scripts found in the QLoRA repo. I wanted it to be as faithful as possible and therefore changed nothing in the training script beyond the model it was pointing to. The model prompt is therefore also the same as the original Guanaco model.
This repo contains the merged f16 model. The QLoRA adaptor can be found here.
A 13b version of the model can be found here.
Legal Disclaimer: This model is bound by the usage restrictions of the original Llama-2 model. And comes with no warranty or gurantees of any kind.
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