tasal9/ZamAI_Pashto_Dataset
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How to use tasal9/ZamAI-QA-Pashto with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="tasal9/ZamAI-QA-Pashto") # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("tasal9/ZamAI-QA-Pashto")
model = AutoModelForCausalLM.from_pretrained("tasal9/ZamAI-QA-Pashto")This repository contains configuration and training metadata for a planned Pashto question-answering / conversational model.
This is not yet a complete loadable model checkpoint. The repo contains config.json and training_config.json, but it does not include model weights or tokenizer files. Loading with AutoModelForCausalLM.from_pretrained(...) will fail until the missing artifacts are uploaded.
config.json: GPT-2 / DialoGPT-style architecture metadatatraining_config.json: intended fine-tuning settingsUpload: