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README.md

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+---
+pipeline_tag: fill-mask
+license: mit
+base_model: FacebookAI/roberta-large
+library_name: kerasformers
+tags:
+- keras
+- kerasformers
+- roberta
+- fill-mask
+- text-encoder
+- arxiv:1907.11692
+- pytorch
+- jax
+- tf
+---
+
+## ***See [our collection](https://huggingface.co/collections/kerasformers/roberta-6a6e8d9b2f4c9253f4145f65) for all versions of RoBERTa.***
+
+# Run RoBERTa with Keras 3: JAX, PyTorch, or TensorFlow
+
+[![GitHub](https://img.shields.io/badge/GitHub-KerasFormers-black?logo=github)](https://github.com/IMvision12/KerasFormers) [![Docs](https://img.shields.io/badge/Docs-RoBERTa-blue)](https://imvision12.github.io/KerasFormers/roberta/) [![Collection](https://img.shields.io/badge/HF-RoBERTa%20collection-yellow)](https://huggingface.co/collections/kerasformers/roberta-6a6e8d9b2f4c9253f4145f65)
+
+# kerasformers/roberta_large
+
+Paper: [RoBERTa: A Robustly Optimized BERT Pretraining Approach (arXiv:1907.11692)](https://arxiv.org/abs/1907.11692) · [HF Papers](https://huggingface.co/papers/1907.11692)
+
+RoBERTa is a robustly optimized BERT encoder: more data/steps, no NSP, dynamic masking, byte-level BPE (mask token `<mask>`), and padding-offset position ids.
+
+For more details on the model, please go to the upstream [model card](https://huggingface.co/FacebookAI/roberta-large).
+
+Pure-**Keras 3** conversion of [`FacebookAI/roberta-large`](https://huggingface.co/FacebookAI/roberta-large) for [kerasformers](https://github.com/IMvision12/KerasFormers). One implementation runs unmodified on **TensorFlow / Torch / JAX**.
+
+This is a **fill-mask / encoder** checkpoint (`RobertaMaskedLM`, large). Task heads load via `hf:` fine-tunes.
+
+## ✨ Quick start (fill-mask)
+
+```python
+import os
+os.environ["KERAS_BACKEND"] = "torch"  # or "jax" / "tensorflow"
+
+from kerasformers.models.roberta import RobertaMaskedLM, RobertaTokenizer
+
+mlm = RobertaMaskedLM.from_weights("kerasformers/roberta_large")
+tokenizer = RobertaTokenizer.from_weights("kerasformers/roberta_large")
+
+inputs = tokenizer("The capital of France is <mask>.")
+logits = mlm(inputs)  # (1, L, vocab_size)
+mask = int((inputs["input_ids"][0] == tokenizer.mask_token_id).argmax())
+print(tokenizer.decode([int(logits[0, mask].argmax())]))
+```
+
+Load any RoBERTa variant the same way with `from_weights("kerasformers/<variant>")`:
+
+| Variant | Hub |
+|---|---|
+| `roberta_base` | [`kerasformers/roberta_base`](https://huggingface.co/kerasformers/roberta_base) |
+| `roberta_large` | [`kerasformers/roberta_large`](https://huggingface.co/kerasformers/roberta_large) |
+
+## Available classes
+
+Load any of these from this repo with `from_weights("kerasformers/roberta_large")` (or on the fly via the `hf:` prefix). The pretrained backbone is shared; task heads not stored in this checkpoint start randomly initialized, ready for fine-tuning (or load a `hf:` fine-tune).
+
+| Class | Task |
+|---|---|
+| `RobertaModel` | Encoder backbone |
+| `RobertaMaskedLM` | Masked language modeling (fill-mask) |
+| `RobertaSequenceClassify` | Sequence classification |
+| `RobertaTokenClassify` | Token classification (NER / POS) |
+| `RobertaQnA` | Extractive question answering |
+| `RobertaMultipleChoice` | Multiple choice |
+
+```python
+from kerasformers.models.roberta import RobertaSequenceClassify
+model = RobertaSequenceClassify.from_weights("kerasformers/roberta_large")
+```
+
+## Tips
+
+- Set `KERAS_BACKEND` **before** importing Keras / kerasformers.
+- Prefer `RobertaTokenizer.from_weights(...)` so BPE vocab matches.
+- Use `<mask>` (not `[MASK]`).
+- See [RoBERTa docs](https://imvision12.github.io/KerasFormers/roberta/) and [Loading Weights](https://imvision12.github.io/KerasFormers/loading_weights/).
+- Community / upstream safetensors still work via the `hf:` prefix, e.g. `RobertaMaskedLM.from_weights("hf:FacebookAI/roberta-large")`.
+
+## Special Thanks
+
+A huge thank you to the Facebook AI RoBERTa authors for creating and releasing these models.
+
+License: MIT.

kf_config.json

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+{
+  "library_name": "kerasformers",
+  "kerasformers_version": "1.2.1",
+  "model_module": "kerasformers.models.roberta",
+  "model_class": "RobertaModel",
+  "variant": "roberta_large",
+  "weights": "model.weights.h5",
+  "schema_version": 2,
+  "weight_dtype": "float32",
+  "model_type": "roberta",
+  "text_config": {
+    "vocab_size": 50265,
+    "embed_dim": 1024,
+    "num_layers": 24,
+    "num_heads": 16,
+    "mlp_dim": 4096,
+    "max_position_embeddings": 514,
+    "type_vocab_size": 1,
+    "hidden_act": "gelu",
+    "layer_norm_eps": 1e-05,
+    "pad_token_id": 1
+  }
+}

model.weights.h5

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