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diff --git a/README.md b/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..ab086c9a655e11797e7399f86efa806c7efa22d7
--- /dev/null
+++ b/README.md
@@ -0,0 +1,159 @@
+---
+library_name: easydel
+pipeline_tag: image-to-text
+tags:
+  - easydel
+  - jax
+  - "gemma4"
+  - "ImageTextToText"
+  - "vanilla"
+---
+
+<p align="center">
+  <img alt="EasyDeL" src="https://raw.githubusercontent.com/erfanzar/easydel/main/images/easydel-logo-with-text.png" height="80">
+</p>
+
+<h1 align="center">google/gemma-4-E4B</h1>
+
+<div align="center">
+  EasyDeL checkpoint converted from google/gemma-4-E4B.
+</div>
+
+## Overview
+
+This checkpoint is intended to be loaded with EasyDeL on JAX (CPU/GPU/TPU). It supports sharded loading with `auto_shard_model=True` and configurable precision via `dtype`, `param_dtype`, and `precision`.
+
+## Quickstart
+
+```python
+import easydel as ed
+from jax import numpy as jnp, lax
+
+repo_id = "/dev/shm/conv/gemma-4-E4B"
+
+dtype = jnp.bfloat16  # try jnp.float16 on many GPUs
+
+model = ed.AutoEasyDeLModelForImageTextToText.from_pretrained(
+    repo_id,
+    dtype=dtype,
+    param_dtype=dtype,
+    precision=lax.Precision("fastest"),
+    sharding_axis_names=("dp", "fsdp", "ep", "tp", "sp"),
+    sharding_axis_dims=(1, -1, 1, 1, 1),
+    config_kwargs=ed.EasyDeLBaseConfigDict(
+        attn_dtype=dtype,
+        attn_mechanism=ed.AttentionMechanisms.VANILLA,
+        fsdp_is_ep_bound=True,
+        sp_is_ep_bound=True,
+        moe_method=ed.MoEMethods.FUSED_MOE,
+    ),
+    auto_shard_model=True,
+    partition_axis=ed.PartitionAxis(),
+)
+```
+
+If the repository only provides PyTorch weights, pass `from_torch=True` to `from_pretrained(...)`.
+
+## Sharding & Parallelism (Multi-Device)
+
+EasyDeL can scale to multiple devices by creating a logical device mesh. Most EasyDeL loaders use a 5D mesh:
+
+- `dp`: data parallel (replicated parameters, different batch shards)
+- `fsdp`: parameter sharding (memory saver; often the biggest axis)
+- `ep`: expert parallel (MoE; keep `1` for non-MoE models)
+- `tp`: tensor parallel (splits large matmuls)
+- `sp`: sequence parallel (splits sequence dimension)
+
+Use `sharding_axis_names=("dp","fsdp","ep","tp","sp")` and choose `sharding_axis_dims` so that their product equals your device count.
+You can use `-1` in `sharding_axis_dims` to let EasyDeL infer the remaining dimension.
+
+<details>
+<summary>Example sharding configs</summary>
+
+```python
+# 8 devices, pure FSDP
+sharding_axis_dims = (1, 8, 1, 1, 1)
+
+# 8 devices, 2-way DP x 4-way FSDP
+sharding_axis_dims = (2, 4, 1, 1, 1)
+
+# 8 devices, 4-way FSDP x 2-way TP
+sharding_axis_dims = (1, 4, 1, 2, 1)
+```
+</details>
+
+## Using via `eLargeModel` (ELM)
+
+`eLargeModel` is a higher-level interface that wires together loading, sharding, training, and eSurge inference from a single config.
+
+```python
+from easydel import eLargeModel
+
+repo_id = "/dev/shm/conv/gemma-4-E4B"
+
+elm = eLargeModel.from_pretrained(repo_id)  # task is auto-detected
+elm.set_dtype("bf16")
+elm.set_sharding(axis_names=("dp", "fsdp", "ep", "tp", "sp"), axis_dims=(1, -1, 1, 1, 1))
+
+model = elm.build_model()
+# Optional: build an inference engine
+# engine = elm.build_esurge()
+```
+
+<details>
+<summary>ELM YAML config example</summary>
+
+```yaml
+model:
+  name_or_path: "/dev/shm/conv/gemma-4-E4B"
+
+loader:
+  dtype: bf16
+  param_dtype: bf16
+
+sharding:
+  axis_dims: [1, -1, 1, 1, 1]
+  auto_shard_model: true
+```
+</details>
+
+## Features
+
+**EasyDeL:**
+- JAX native implementation and sharded execution
+- Configurable attention backends via `AttentionMechanisms.*`
+- Precision control via `dtype`, `param_dtype`, and `precision`
+
+## Installation
+
+```bash
+pip install easydel
+```
+
+## Links
+
+- EasyDeL GitHub: https://github.com/erfanzar/EasyDeL
+- Docs: https://easydel.readthedocs.io/en/latest/
+
+## Supported Tasks
+
+- ImageTextToText
+
+## Limitations
+
+- Refer to the original model card for training data, evaluation, and intended use.
+
+## License
+
+EasyDeL is released under the Apache-2.0 license. The license for this model's weights may differ; please consult the original repository.
+
+## Citation
+
+```bibtex
+@misc{Zare Chavoshi_2023,
+    title={EasyDeL: An open-source library for enhancing and streamlining the training process of machine learning models},
+    url={https://github.com/erfanzar/EasyDeL},
+    author={Zare Chavoshi, Erfan},
+    year={2023}
+}
+```
diff --git a/checkpoint_metadata.json b/checkpoint_metadata.json
new file mode 100644
index 0000000000000000000000000000000000000000..4156f8f36804858b658c45d2dff8db05329f50cc
--- /dev/null
+++ b/checkpoint_metadata.json
@@ -0,0 +1,6 @@
+{
+  "timestamp": "2026-04-09T03:44:41.226750",
+  "custom_metadata": {
+    "step": 0
+  }
+}
\ No newline at end of file
diff --git a/config.json b/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..4495073b7487049de523437ed2c1617005822d58
--- /dev/null
+++ b/config.json
@@ -0,0 +1,510 @@
+{
+  "_external_rope_config_kwargs": {},
+  "add_cross_attention": false,
+  "architectures": [
+    "Gemma4ForConditionalGeneration"
+  ],
+  "attn_mechanism": "vanilla",
+  "audio_config": {
+    "_name_or_path": "",
+    "architectures": null,
+    "attention_chunk_size": 12,
+    "attention_context_left": 13,
+    "attention_context_right": 0,
+    "attention_invalid_logits_value": -1000000000.0,
+    "attention_logit_cap": 50.0,
+    "chunk_size_feed_forward": 0,
+    "conv_kernel_size": 5,
+    "dtype": "bfloat16",
+    "gradient_clipping": 10000000000.0,
+    "hidden_act": "silu",
+    "hidden_size": 1024,
+    "id2label": {
+      "0": "LABEL_0",
+      "1": "LABEL_1"
+    },
+    "initializer_range": 0.02,
+    "is_encoder_decoder": false,
+    "label2id": {
+      "LABEL_0": 0,
+      "LABEL_1": 1
+    },
+    "model_type": "gemma4_audio",
+    "num_attention_heads": 8,
+    "num_hidden_layers": 12,
+    "output_attentions": false,
+    "output_hidden_states": false,
+    "output_proj_dims": 1536,
+    "problem_type": null,
+    "residual_weight": 0.5,
+    "return_dict": true,
+    "rms_norm_eps": 1e-06,
+    "subsampling_conv_channels": [
+      128,
+      32
+    ],
+    "use_clipped_linears": true
+  },
+  "audio_token_id": 258881,
+  "backend": null,
+  "bits": null,
+  "blocksize_b": 1,
+  "blocksize_k": 512,
+  "blocksize_q": 512,
+  "boa_token_id": 256000,
+  "boi_token_id": 255999,
+  "bos_token_id": null,
+  "cross_attention_hidden_size": null,
+  "decode_attn_mechanism": null,
+  "decoder_start_token_id": null,
+  "dtype": "bfloat16",
+  "easy_method": "train",
+  "eoa_token_id": 258883,
+  "eoa_token_index": 258883,
+  "eoi_token_id": 258882,
+  "eos_token_id": null,
+  "fcm_max_ratio": 0.0,
+  "fcm_min_ratio": 0.0,
+  "flash_attention_backward_pass_impl": "triton",
+  "fsdp_is_ep_bound": true,
+  "gradient_checkpointing": "",
+  "gradient_checkpointing_targets": null,
+  "hardware_abstraction": false,
+  "image_token_id": 258880,
+  "initializer_range": 0.02,
+  "is_decoder": false,
+  "kv_cache_quantization_config": null,
+  "kv_cache_sharding_sequence_axis_name": "sp",
+  "kvdtype": "bfloat16",
+  "lmhead_chunksize": null,
+  "max_position_embeddings": null,
+  "mla_attn_dtype": "bfloat16",
+  "mla_attn_mechanism": "auto",
+  "mla_attn_softmax_dtype": "float32",
+  "model_type": "gemma4",
+  "moe_force_xla_gmm": false,
+  "moe_method": "fused_moe",
+  "moe_tiling_size_batch": 4,
+  "moe_tiling_size_dim": 128,
+  "moe_tiling_size_seqlen": 128,
+  "operation_configs": null,
+  "pad_token_id": null,
+  "pallas_k_block_size": 128,
+  "pallas_m_block_size": 128,
+  "pallas_n_block_size": 128,
+  "partition_axis": {
+    "attention_dim_axis": null,
+    "attention_kv_dim_axis": null,
+    "batch_axis": [
+      "fsdp",
+      "dp"
+    ],
+    "bias_head_sequence_axis": null,
+    "bias_key_sequence_axis": null,
+    "data_parallel_axis": "dp",
+    "decode_attention_dim_axis": null,
+    "decode_attention_kv_dim_axis": null,
+    "decode_batch_axis": [
+      "fsdp",
+      "dp"
+    ],
+    "decode_head_axis": "tp",
+    "decode_key_sequence_axis": "sp",
+    "decode_kv_head_axis": "tp",
+    "decode_query_sequence_axis": null,
+    "expert_axis": "ep",
+    "expert_gate_axis": null,
+    "expert_parallel_axis": "ep",
+    "fully_sharded_data_parallel_axis": "fsdp",
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+    "hidden_state_axis": "tp",
+    "key_sequence_axis": "sp",
+    "kv_head_axis": "tp",
+    "mlp_intermediate_axis": "tp",
+    "query_sequence_axis": "sp",
+    "sequence_axis": "sp",
+    "sequence_parallel_axis": "sp",
+    "tensor_parallel_axis": "tp",
+    "vocab_axis": "tp"
+  },
+  "platform": null,
+  "precompute_masks": true,
+  "pretraining_tp": 1,
+  "qmm_platform_override": null,
+  "qmm_tpu_path_override": null,
+  "quantization_config": null,
+  "scan_attention_layers": false,
+  "scan_mlp_chunk_size": 1024,
+  "scan_ring_attention": true,
+  "sep_token_id": null,
+  "sequence_axis_name": "sp",
+  "sharding_axis_dims": [
+    1,
+    -1,
+    1,
+    1,
+    1
+  ],
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+    "attention_dropout": 0.0,
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+    "gradient_checkpointing": "",
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+    "kv_cache_quantization_config": null,
+    "kv_cache_sharding_sequence_axis_name": "sp",
+    "kvdtype": "bfloat16",
+    "layer_types": [
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+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
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+    "max_position_embeddings": 131072,
+    "mla_attn_dtype": "bfloat16",
+    "mla_attn_mechanism": "auto",
+    "mla_attn_softmax_dtype": "float32",
+    "model_type": "gemma4_text",
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+  "bos_token": "<bos>",
+  "eoa_token": "<audio|>",
+  "eoc_token": "<channel|>",
+  "eoi_token": "<image|>",
+  "eos_token": "<eos>",
+  "eot_token": "<turn|>",
+  "escape_token": "<|\"|>",
+  "etc_token": "<tool_call|>",
+  "etd_token": "<tool|>",
+  "etr_token": "<tool_response|>",
+  "extra_special_tokens": [
+    "<|video|>"
+  ],
+  "image_token": "<|image|>",
+  "is_local": false,
+  "mask_token": "<mask>",
+  "model_max_length": 1000000000000000019884624838656,
+  "model_specific_special_tokens": {
+    "audio_token": "<|audio|>",
+    "boa_token": "<|audio>",
+    "boi_token": "<|image>",
+    "eoa_token": "<audio|>",
+    "eoc_token": "<channel|>",
+    "eoi_token": "<image|>",
+    "eot_token": "<turn|>",
+    "escape_token": "<|\"|>",
+    "etc_token": "<tool_call|>",
+    "etd_token": "<tool|>",
+    "etr_token": "<tool_response|>",
+    "image_token": "<|image|>",
+    "soc_token": "<|channel>",
+    "sot_token": "<|turn>",
+    "stc_token": "<|tool_call>",
+    "std_token": "<|tool>",
+    "str_token": "<|tool_response>",
+    "think_token": "<|think|>"
+  },
+  "pad_token": "<pad>",
+  "padding_side": "left",
+  "processor_class": "Gemma4Processor",
+  "soc_token": "<|channel>",
+  "sot_token": "<|turn>",
+  "stc_token": "<|tool_call>",
+  "std_token": "<|tool>",
+  "str_token": "<|tool_response>",
+  "think_token": "<|think|>",
+  "tokenizer_class": "GemmaTokenizer",
+  "unk_token": "<unk>"
+}