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Model: tirumalaseti/slm-125m-base Source: Original Platform
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README.md
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README.md
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---
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- text-generation
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- causal-lm
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- llama
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- legal
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- finance
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- modal
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---
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# tirumalaseti/slm-125m-base
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This is a **125M-parameter base completion model** trained from scratch on a legal/financial-heavy corpus. It is **not a chatbot**: it was optimized for next-token prediction and works best when prompted with the opening of a sentence or paragraph to continue.
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## Model summary
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- **Trainable parameters:** 125,847,552 (~125.848M)
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- **Architecture:** 12-layer Llama-style decoder, 768 hidden size, 12 attention heads
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- **Context length:** 1,024 tokens
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- **Tokenizer:** 16,384-token byte-level BPE
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- **Training tokens seen:** 2,500,329,472
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- **Optimizer steps:** 4,769
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- **Completed epochs over the packed train set:** 1.23
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- **Final validation loss:** 2.3035
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- **Final validation perplexity:** 10.01
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- **Reported spend:** $0.00
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## Training corpus
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The packed corpus used for pretraining contains 2,059,674,624 total tokens:
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- **Train:** 2,039,072,768
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- **Validation:** 20,601,856
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Realized source mix:
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- **US case law:** 722,081,792 tokens (35.1%)
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- **SEC filings:** 868,714,496 tokens (42.2%)
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- **Educational web text:** 468,878,336 tokens (22.8%)
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_id = "tirumalaseti/slm-125m-base"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id)
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prompt = "The plaintiff respectfully moves this Court to"
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inputs = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(**inputs, max_new_tokens=96, temperature=0.8, top_p=0.95)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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## Notes
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- This is a **base model**, not an instruction-tuned assistant.
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- It is strongest at continuing legal/financial prose in-register.
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- The spend figure comes from the latest visible Modal billing report; Modal billing report may lag; this value reflects the latest locally visible report..
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config.json
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config.json
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{
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 0,
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"eos_token_id": 1,
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"head_dim": 64,
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"hidden_act": "silu",
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"max_position_embeddings": 1024,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"num_key_value_heads": 12,
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"pad_token_id": 2,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"tie_word_embeddings": true,
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"torch_dtype": "float32",
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"transformers_version": "4.46.3",
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"use_cache": true,
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"vocab_size": 16384
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}
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generation_config.json
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 0,
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"pad_token_id": 2,
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"transformers_version": "4.46.3"
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}
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model-metadata.json
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model-metadata.json
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{
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"model_id": "tirumalaseti/slm-125m-base",
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"project": "slm-125m",
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"parameter_count": 125847552,
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"parameter_count_millions": 125.848,
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"context_length": 1024,
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"vocab_size": 16384,
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"train_tokens": 2039072768,
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"val_tokens": 20601856,
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"total_tokens": 2059674624,
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"tokens_seen": 2500329472,
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"optimizer_steps": 4769,
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"epochs_completed": 1.226,
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"world_size": 8,
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"grad_accum_steps": 2,
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"final_validation_loss": 2.303484795203459,
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"final_validation_perplexity": 10.00900107062853,
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"reported_spend_usd": 0.0,
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"reported_spend_note": "Modal billing report may lag; this value reflects the latest locally visible report.",
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"corpus_mix_tokens": {
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"case-law": 722081792,
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"sec": 868714496,
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"fineweb-edu": 468878336
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}
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 503405488
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special_tokens_map.json
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special_tokens_map.json
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{
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"additional_special_tokens": [
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"<|user|>",
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"<|assistant|>",
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}
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tokenizer.json
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tokenizer.json
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tokenizer_config.json
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tokenizer_config.json
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{
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"added_tokens_decoder": {
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"0": {
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"<|system|>"
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"bos_token": "<|bos|>",
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"clean_up_tokenization_spaces": false,
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"tokenizer_class": "PreTrainedTokenizerFast",
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"unk_token": "<|unk|>"
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}
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training_summary.json
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{
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"step": 4769,
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"grad_accum_steps": 2,
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"last_eval_loss": 2.303484795203459
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}
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