Faithful PyTorch conversion of NepBERTa/NepBERTa tf_model.h5

README.md

@@ -0,0 +1,46 @@
+---
+language: ne
+license: cc-by-4.0
+base_model: NepBERTa/NepBERTa
+tags:
+  - nepali
+  - bert
+  - pytorch-conversion
+---
+
+# NepBERTa — PyTorch conversion
+
+A faithful PyTorch conversion of the official
+[NepBERTa/NepBERTa](https://huggingface.co/NepBERTa/NepBERTa) checkpoint,
+which ships only TensorFlow weights (`tf_model.h5`) that transformers v5
+can no longer load.
+
+## Provenance
+
+- Source: `NepBERTa/NepBERTa` @ `tf_model.h5` (TFBertForMaskedLM, 207 tensors).
+- Converted 2026-08-04 with `transformers 4.57.6` / `tensorflow-cpu 2.21.0`
+  via `load_tf2_checkpoint_in_pytorch_model` into a `BertModel`.
+- Tokenizer files copied unmodified from the source repo
+  (`vocab.txt` md5 `edfd394677436b306fb062159ec46c72`).
+- This repo contains **only the 197 backbone tensors present in the
+  official checkpoint** — the source has no trained pooler (it is a
+  masked-LM checkpoint), so no pooler weights are shipped; downstream
+  loading initializes the pooler freshly, exactly as loading the
+  official checkpoint would.
+- Cross-check: every converted tensor is bit-identical
+  (`torch.equal`) to the independent community port
+  [Rajan/nepbertaTorch](https://huggingface.co/Rajan/nepbertaTorch)
+  on all 198 tensors that repo shares with the official checkpoint.
+
+## Use
+
+```python
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+tok = AutoTokenizer.from_pretrained("subrace/NepBERTa-pytorch")
+model = AutoModelForSequenceClassification.from_pretrained(
+    "subrace/NepBERTa-pytorch", num_labels=2)
+```
+
+All credit for the model itself goes to the NepBERTa authors
+([paper](https://aclanthology.org/2022.aacl-short.34/)); this repo exists
+only so the weights load in modern PyTorch-only transformers.

config.json

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+{
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_hidden_state": true,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.57.6",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:78748788583aa5822ead109ad06c18386309e93603ede7505173aeccc2fbc0d6
+size 435588776

special_tokens_map.json

@@ -0,0 +1,7 @@
+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

@@ -0,0 +1,58 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "4": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}