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PredictiveManish
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Trimurti-LM

Text Generation
Transformers
Safetensors
English
Hindi
Panjabi
language_model
multilingual
indic-languages
hindi
punjabi
small-model
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Trimurti-LM
File size: 3,175 Bytes
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{
	"model_id": "trimurti-lm",
	"model_name": "Trimurti-LM",
	"model_type": "language_model",
	"architecture": "GPT2",
	"framework": "transformers",
	
	"languages": {
		"supported": ["en", "hi", "pa"],
		"language_tags": ["[EN]", "[HI]", "[PA]"],
		"description": "Trilingual language model supporting English, Hindi, and Punjabi"
	},
	
	"model_config": {
		"vocab_size": 8000,
		"n_positions": 128,
		"n_embd": 256,
		"n_layer": 4,
		"n_head": 4,
		"n_inner": 512,
		"activation_function": "gelu_new",
		"attn_pdrop": 0.1,
		"embd_pdrop": 0.1,
		"resid_pdrop": 0.1,
		"estimated_parameters": "4.7M"
	},
	
	"tokenizer": {
		"type": "sentencepiece",
		"model_type": "unigram",
		"vocab_size": 8000,
		"character_coverage": 0.9995,
		"byte_fallback": true,
		"model_path": "final_corpus/multilingual_spm.model"
	},
	
	"training": {
		"corpus": "final_corpus/multilingual_corpus_train.txt",
		"validation": "final_corpus/multilingual_corpus_val.txt",
		"total_steps": 5000,
		"batch_size": 2,
		"gradient_accumulation": 8,
		"learning_rate": 2e-4,
		"warmup_steps": 1000,
		"effective_batch_size": 16
	},
	
	"checkpoints": {
		"path": "checkpoints_tiny",
		"available_checkpoints": [
			"step1000",
			"step2000",
			"step3000",
			"step4000",
			"step5000",
			"final"
		]
	},
	
	"evaluation": {
		"overall_accuracy": 100.0,
		"english_accuracy": 100.0,
		"hindi_accuracy": 100.0,
		"punjabi_accuracy": 100.0,
		"mixed_accuracy": 100.0,
		"avg_english_perplexity": 42.29,
		"avg_hindi_perplexity": 50.56,
		"avg_punjabi_perplexity": 63.42
	},
	
	"entry_points": {
		"training": "python train_model.py",
		"testing": "python test_model.py",
		"evaluation": "python evaluate_model.py",
		"preprocessing": "python preprocess.py",
		"web_interface": "python web_interface.py"
	},
	
	"dependencies": [
		"torch",
		"transformers",
		"sentencepiece",
		"tqdm",
		"gradio",
		"pandas",
		"numpy"
	],
	
	"filter": [
		{
			"bool": {
				"should": [
					{
						"term": { "path": "model_index.json" }
					},
					{
						"regexp": { "path": "[^/]*\\.safetensors" }
					},
					{
						"regexp": { "path": "[^/]*\\.ckpt" }
					},
					{
						"regexp": { "path": "[^/]*\\.bin" }
					}
				],
				"minimum_should_match": 1
			}
		}
	],
	
	"files": [
		{
			"path": "checkpoints_tiny/final/model.safetensors",
			"description": "Final trained model weights"
		},
		{
			"path": "checkpoints_tiny/final/config.json",
			"description": "Model configuration"
		},
		{
			"path": "checkpoints_tiny/final/generation_config.json",
			"description": "Generation settings"
		},
		{
			"path": "final_corpus/multilingual_spm.model",
			"description": "SentencePiece tokenizer model"
		},
		{
			"path": "final_corpus/multilingual_spm.vocab",
			"description": "Tokenizer vocabulary"
		},
		{
			"path": "train_model.py",
			"description": "Training script"
		},
		{
			"path": "test_model.py",
			"description": "Testing and inference script"
		},
		{
			"path": "evaluate_model.py",
			"description": "Evaluation script"
		},
		{
			"path": "preprocess.py",
			"description": "Data preprocessing script"
		},
		{
			"path": "web_interface.py",
			"description": "Gradio web interface"
		}
	]
}