How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="solidrust/flammen17-py-DPO-v1-7B-AWQ")
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("solidrust/flammen17-py-DPO-v1-7B-AWQ")
model = AutoModelForCausalLM.from_pretrained("solidrust/flammen17-py-DPO-v1-7B-AWQ", device_map="auto")
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Configuration Parsing Warning:In config.json: "quantization_config.modules_to_not_convert" must be an array

nbeerbower/flammen17-py-DPO-v1-7B AWQ

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Model Summary

A Mistral 7B LLM built from merging pretrained models and finetuning on Jon Durbin's py-dpo-v0.1.

Finetuned using an A100 on Google Colab. 🙏

Fine-tune a Mistral-7b model with Direct Preference Optimization - Maxime Labonne

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