Slm 125m Base
A 125M-parameter Llama-style base language model, pretrained from scratch on a legal/financial corpus (US case law + SEC filings + a web slice, 2.19B tokens).
Fonte do modelo
- Tipo
- Text model
- Tamanho do arquivo
- 240 MB
- Versão
- vmodel
- Atualizado
- 19 de out. de 2026
- Downloads
- 275
- Fonte
- Hugging Face
Descrição da fonte
slm-125m-base
A 125M-parameter Llama-style base language model, pretrained from scratch on a legal/financial corpus (US case law + SEC filings + a web slice, ~2.19B tokens).
- Pretraining: 10 epochs, 8xH100. Held-out validation perplexity: 8.36.
- This is a base COMPLETER, not a chat model. Prompt it with the start of a sentence and it continues in the legal register. It speaks the register fluently but does not know facts (knowledge is capped at ~2 bits/param at this size).
from transformers import AutoModelForCausalLM, AutoTokenizer
tok = AutoTokenizer.from_pretrained("thesreedath/slm-125m-base")
model = AutoModelForCausalLM.from_pretrained("thesreedath/slm-125m-base")
ids = tok("The plaintiff alleges that the defendant", return_tensors="pt").input_ids
print(tok.decode(model.generate(ids, max_new_tokens=60, do_sample=True,
temperature=0.8, min_new_tokens=40)[0]))
Full pipeline + fine-tuning code: https://github.com/Vizuara-AI-Lab/slm-125m-from-scratch
Fontes
1 fonte
Fontes
1 fonteVerificado 8 de ago.
Artefatos de modelo
1 artefato
Artefatos de modelo
1 artefatoTrechos de fonte
3 trechos
Trechos de fonte
3 trechos--- license: other language: en tags: [legal, from-scratch, llama, small-language-model] --- # slm-125m-base A **125M-parameter Llama-style base language model**, pretrained **from scratch** on a legal/financial corpus (US case law + SEC filings + a web slice, ~2.19B tokens). - **Pretraining:** 10 epochs, 8xH100. **Held-out validation perplexity: 8.36**. - **This is a base COMPLETER, not a chat model.** Prompt it with the start of a sentence and it continues in the legal register. It speaks the register fluently but does not know facts (knowledge is capped at ~2 bits/param at this size). ```python from transformers import AutoModelForCausalLM, AutoTokenizer tok = AutoTokenizer.from_pretrained("thesreedath/slm-125m-base") model = AutoModelForCausalLM.from_pretrained("thesreedath/slm-125m-base") ids = tok("The plaintiff alleges that the defendant", return_tensors="pt").input_ids print(tok.decode(model.generate(ids, max_new_tokens=60, do_sample=True, temperature=0.8, min_new_tokens=40)[0])) ``` Full pipeline + fine-tuning code: https://github.com/Vizuara-AI-Lab/slm-125m-from-scratch
Source context: 275 downloads · 1 likes · Repo thesreedath/slm-125m-base
Source context: 145 downloads · 1 likes · Repo thesreedath/slm-125m-base
