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--- |
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license: apache-2.0 |
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pipeline_tag: text-generation |
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library_name: peft |
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--- |
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## Hindi-wiki-LLaMA |
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Hindi Wikipedia Article Generation Model |
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This repository contains a language generation model trained on Hindi Wikipedia articles using the Hugging Face Transformers library. The model is based on the Llama-2 architecture and fine-tuned on a large dataset of Hindi text from Wikipedia. |
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## Model Details |
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- Base Model: Llama-2 |
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- Pretraining Dataset: Hindi Wikipedia Articles |
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- Tokenizer: Hugging Face Tokenizer |
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- Model Architecture: Causal Language Modeling |
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```python |
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from peft import AutoPeftModelForCausalLM |
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base_model_name = "meta-llama/Llama-2-7b-hf" |
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tokenizer = AutoTokenizer.from_pretrained(base_model_name, trust_remote_code=True) |
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tokenizer.pad_token = tokenizer.eos_token |
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output_dir = "./final_checkpoint" |
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device_map = {"": 0} |
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model = AutoPeftModelForCausalLM.from_pretrained(output_dir, device_map=device_map, torch_dtype=torch.bfloat16) |
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device = torch.device("cuda") |
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text = "" |
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inputs = tokenizer(text, return_tensors="pt").to(device) |
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outputs = model.generate(input_ids=inputs["input_ids"].to("cuda"), attention_mask=inputs["attention_mask"], max_new_tokens=100, pad_token_id=tokenizer.eos_token_id) |
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print(tokenizer.decode(outputs[0][len(inputs["input_ids"][0]):], skip_special_tokens=True)) |
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``` |
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## Model Performance:-- |
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The model has been trained on a substantial amount of Hindi Wikipedia articles, which allows it to generate coherent and contextually relevant text. |
