Samhita/slack-data-long-responses
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How to use MatrixNinja/slackGPT-ft with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("TheBloke/Mistral-7B-Instruct-v0.2-GPTQ")
model = PeftModel.from_pretrained(base_model, "MatrixNinja/slackGPT-ft")Configuration Parsing Warning:In adapter_config.json: "peft.base_model_name_or_path" must be a string
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on the None dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9733 | 1.0 | 550 | 0.9338 |
Base model
mistralai/Mistral-7B-Instruct-v0.2