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anlp-a2-part1-dense
neemon/anlp-a2-part1-dense
anlp-a2-part1-dense is a translation model from neemon. Use it when you need text moved from one language to another. It is set up for pytorch. The card lists the license as mit.
Decoder-only transformer with dense two-layer MLP feed-forward (the baseline).
Access
Public
Updated Oct 1, 2026
Repo size
333 MB
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Repo makeup
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.pt166 MB · 98%
At a glance
- Task
- Translation
- Library
- pytorch
- License
- mit
- Access
- Public
- Created
- Sep 14, 2026
- Updated
- Oct 1, 2026
- SHA
- 726cec3c
Try a prompt
Model card
From the Hugging Face model README
ANLP Assignment 2 (part1): dense
Decoder-only transformer with dense two-layer MLP feed-forward (the baseline).
Trained from scratch for IIIT-H Advanced NLP, Monsoon 2026. Architecture, training code and evaluation live in the assignment repository. This repository holds the checkpoint and the tokenizer it was trained with, which every model in the assignment shares.
Architecture
| Setting | Value |
|---|---|
d_model | 512 |
n_layers | 8 |
n_heads | 8 |
n_kv_heads | 8 |
n_ctx | 256 |
vocab_size | 32000 |
ffn | dense |
d_ff | 2048 |
n_routed_experts | 0 |
n_shared_experts | 0 |
top_k | 0 |
norm | rmsnorm |
Parameters
| Count | Value |
|---|---|
| Total | 41,579,008 |
| Active per token | 41,579,008 |
| Feed-forward (total / active) | 16,797,696 / 16,797,696 |
Test set results
| Metric | Value |
|---|---|
| Perplexity (both directions) | 9.27 |
| BLEU vi->en | 35.25 |
| BLEU ja->en | 25.45 |
| BLEU mean | 30.35 |
Training
- Scored target tokens: 33,393,292
- Best validation loss: 1.9864
- Best validation perplexity: 7.29
Loading
import torch
payload = torch.load("model.pt", map_location="cpu", weights_only=False)
state_dict, config = payload["model"], payload["config"]
from tokenizers import Tokenizer
tokenizer = Tokenizer.from_file("tokenizer.json")
- Task
- Translation
- Library
- pytorch
- License
- mit
- Languages
- en, vi, ja
- Created
- Sep 14, 2026
- Updated
- Oct 1, 2026