Publish Falcon model packs v1.0.0

.gitattributes

@@ -33,3 +33,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+allam/allam-7b-instruct-preview-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+marian/en-ar/source.spm filter=lfs diff=lfs merge=lfs -text
+marian/en-ar/target.spm filter=lfs diff=lfs merge=lfs -text
+marian/ar-en/source.spm filter=lfs diff=lfs merge=lfs -text
+marian/ar-en/target.spm filter=lfs diff=lfs merge=lfs -text

LICENSE.md

@@ -0,0 +1,38 @@
+# Model licenses and attribution
+
+Each pack retains its original license; there is no single replacement license
+for all weights in this repository.
+
+## ALLaM
+
+`allam/*` derives from [humain-ai/ALLaM-7B-Instruct-preview](https://huggingface.co/humain-ai/ALLaM-7B-Instruct-preview)
+at revision `a28dd1e67420cde72d3629c8633a974cf7d9c366`, originally developed by
+the National Center for Artificial Intelligence (NCAI), Saudi Data and AI
+Authority (SDAIA). The pinned upstream model card declares Apache-2.0 and
+contains no separate LICENSE or NOTICE file. Its model card is preserved at
+[sources/allam-README.md](sources/allam-README.md).
+
+Falcon converted the model to GGUF and quantized it to Q4_K_M using llama.cpp
+revision `58367713a6935c0810103378144008df32e3d5db`. The tokenizer/config files
+retain their upstream content. See [Apache-2.0](licenses/Apache-2.0.txt).
+
+## OPUS-MT / Marian
+
+`marian/en-ar/*` and `marian/ar-en/*` derive from:
+
+- [Helsinki-NLP/opus-mt-tc-big-en-ar](https://huggingface.co/Helsinki-NLP/opus-mt-tc-big-en-ar), revision `ae9f1b2fd512000ca9440eb3b8ec9aa9acb298ac`.
+- [Helsinki-NLP/opus-mt-tc-big-ar-en](https://huggingface.co/Helsinki-NLP/opus-mt-tc-big-ar-en), revision `bcb4acd39ee8e3552e171653a8e31a10729b4330`.
+
+Attribution: Helsinki-NLP / OPUS-MT project, University of Helsinki, and the
+authors/citations identified in the preserved original cards at
+[sources/marian-en-ar-README.md](sources/marian-en-ar-README.md) and
+[sources/marian-ar-en-README.md](sources/marian-ar-en-README.md).
+
+Both upstream model cards declare CC-BY-4.0. Falcon converted the weights to
+CTranslate2 format and quantized them to int8, without additional fine-tuning.
+The SentencePiece models are copied from upstream. See
+[CC-BY-4.0](licenses/CC-BY-4.0.txt) and the
+[license summary](https://creativecommons.org/licenses/by/4.0/).
+
+Original authors do not endorse Falcon or these conversions. Preserve these
+attributions, license texts, and modification notices when redistributing packs.

README.md

@@ -0,0 +1,66 @@
+---
+language:
+- en
+- ar
+license: other
+license_name: apache-2.0-and-cc-by-4.0-per-pack
+license_link: LICENSE.md
+base_model:
+- humain-ai/ALLaM-7B-Instruct-preview
+- Helsinki-NLP/opus-mt-tc-big-en-ar
+- Helsinki-NLP/opus-mt-tc-big-ar-en
+tags:
+- falcon
+- gguf
+- ctranslate2
+- translation
+- quantized
+---
+
+# Falcon model packs
+
+Prepared English/Arabic model artifacts for the Falcon desktop application.
+This is a multi-pack distribution repository, not a single Transformers model.
+No Hugging Face account is required to download these public files.
+
+| Pack | Files | Runtime | Changes from upstream | License |
+| --- | --- | --- | --- | --- |
+| ALLaM-7B-Instruct-preview | `allam/` | llama.cpp | Converted to GGUF and quantized Q4_K_M | Apache-2.0 |
+| OPUS-MT English → Arabic | `marian/en-ar/` | CTranslate2 | Converted to CTranslate2 and quantized int8 | CC-BY-4.0 |
+| OPUS-MT Arabic → English | `marian/ar-en/` | CTranslate2 | Converted to CTranslate2 and quantized int8 | CC-BY-4.0 |
+
+ALLaM is attributed to its original authors at NCAI/SDAIA; its upstream
+repository is maintained under HUMAIN. OPUS-MT is attributed to Helsinki-NLP /
+the OPUS-MT project, University of Helsinki. See the original model cards in
+`sources/` for authorship, citations, intended uses, and limitations. Falcon's
+packaging does not imply endorsement by the original authors.
+
+`manifest.json` records the exact upstream revisions, artifact sizes and SHA-256
+hashes. Original model cards are preserved in `sources/`; applicable license
+texts and attribution are linked in [LICENSE.md](LICENSE.md). The transformations
+are format conversion and quantization, with no additional fine-tuning.
+The exact Marian converter environment was not recorded for these existing
+artifacts; their identity is fixed by hashes. Future conversions should record
+the complete toolchain versions before publishing a new release.
+
+## Downloading
+
+Use a full **commit SHA** from the release history, rather than `main` or a
+mutable tag, and verify the file size and SHA-256 before loading. For example:
+
+```text
+https://huggingface.co/anushkrishna/falcon-models/resolve/<commit-sha>/marian/en-ar/model.bin
+https://huggingface.co/anushkrishna/falcon-models/resolve/<commit-sha>/allam/allam-7b-instruct-preview-Q4_K_M.gguf
+```
+
+Marian requires all five files in the selected direction folder. ALLaM's
+tokenizer/config files are supplied alongside its GGUF for provenance and
+compatibility. The GGUF includes the tokenizer and chat template.
+
+OCR continues to use the official PaddlePaddle Hugging Face repositories;
+`external_artifacts` in the manifest documents Falcon's pinned OCR weights.
+Those weights and native runtime binaries are not mirrored in this release.
+
+Falcon downloads model data during setup and runs document processing locally.
+Model updates should be tested and explicitly approved by the application
+release; uploading new files here does not update an already pinned app.

allam/allam-7b-instruct-preview-Q4_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e71791258a787ebe5d14c4bb01b7403d6390ada51e50e146899fae6db965cdc2
+size 4263194080

allam/config.json

@@ -0,0 +1,28 @@
+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.006,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 4096,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 32,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.39.3",
+  "use_cache": true,
+  "vocab_size": 64000,
+  "internal_version": "7b-alpha-v2.33.0.30"
+}

allam/tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:feff3deb3537c4a47b77585053ad2aa00484da7907b188e0111cbed1f4592e67
+size 1228714

allam/tokenizer_config.json

@@ -0,0 +1,36 @@
+{
+  "add_bos_token": false,
+  "add_eos_token": false,
+  "bos_token": {
+    "__type": "AddedToken",
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\\n' + system_message + '\\n<</SYS>>\\n\\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + ' [INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' '  + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": {
+    "__type": "AddedToken",
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "legacy": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": null,
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": {
+    "__type": "AddedToken",
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

licenses/Apache-2.0.txt

@@ -0,0 +1,202 @@
+
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
+      and distribution as defined by Sections 1 through 9 of this document.
+
+      "Licensor" shall mean the copyright owner or entity authorized by
+      the copyright owner that is granting the License.
+
+      "Legal Entity" shall mean the union of the acting entity and all
+      other entities that control, are controlled by, or are under common
+      control with that entity. For the purposes of this definition,
+      "control" means (i) the power, direct or indirect, to cause the
+      direction or management of such entity, whether by contract or
+      otherwise, or (ii) ownership of fifty percent (50%) or more of the
+      outstanding shares, or (iii) beneficial ownership of such entity.
+
+      "You" (or "Your") shall mean an individual or Legal Entity
+      exercising permissions granted by this License.
+
+      "Source" form shall mean the preferred form for making modifications,
+      including but not limited to software source code, documentation
+      source, and configuration files.
+
+      "Object" form shall mean any form resulting from mechanical
+      transformation or translation of a Source form, including but
+      not limited to compiled object code, generated documentation,
+      and conversions to other media types.
+
+      "Work" shall mean the work of authorship, whether in Source or
+      Object form, made available under the License, as indicated by a
+      copyright notice that is included in or attached to the work
+      (an example is provided in the Appendix below).
+
+      "Derivative Works" shall mean any work, whether in Source or Object
+      form, that is based on (or derived from) the Work and for which the
+      editorial revisions, annotations, elaborations, or other modifications
+      represent, as a whole, an original work of authorship. For the purposes
+      of this License, Derivative Works shall not include works that remain
+      separable from, or merely link (or bind by name) to the interfaces of,
+      the Work and Derivative Works thereof.
+
+      "Contribution" shall mean any work of authorship, including
+      the original version of the Work and any modifications or additions
+      to that Work or Derivative Works thereof, that is intentionally
+      submitted to Licensor for inclusion in the Work by the copyright owner
+      or by an individual or Legal Entity authorized to submit on behalf of
+      the copyright owner. For the purposes of this definition, "submitted"
+      means any form of electronic, verbal, or written communication sent
+      to the Licensor or its representatives, including but not limited to
+      communication on electronic mailing lists, source code control systems,
+      and issue tracking systems that are managed by, or on behalf of, the
+      Licensor for the purpose of discussing and improving the Work, but
+      excluding communication that is conspicuously marked or otherwise
+      designated in writing by the copyright owner as "Not a Contribution."
+
+      "Contributor" shall mean Licensor and any individual or Legal Entity
+      on behalf of whom a Contribution has been received by Licensor and
+      subsequently incorporated within the Work.
+
+   2. Grant of Copyright License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      copyright license to reproduce, prepare Derivative Works of,
+      publicly display, publicly perform, sublicense, and distribute the
+      Work and such Derivative Works in Source or Object form.
+
+   3. Grant of Patent License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      (except as stated in this section) patent license to make, have made,
+      use, offer to sell, sell, import, and otherwise transfer the Work,
+      where such license applies only to those patent claims licensable
+      by such Contributor that are necessarily infringed by their
+      Contribution(s) alone or by combination of their Contribution(s)
+      with the Work to which such Contribution(s) was submitted. If You
+      institute patent litigation against any entity (including a
+      cross-claim or counterclaim in a lawsuit) alleging that the Work
+      or a Contribution incorporated within the Work constitutes direct
+      or contributory patent infringement, then any patent licenses
+      granted to You under this License for that Work shall terminate
+      as of the date such litigation is filed.
+
+   4. Redistribution. You may reproduce and distribute copies of the
+      Work or Derivative Works thereof in any medium, with or without
+      modifications, and in Source or Object form, provided that You
+      meet the following conditions:
+
+      (a) You must give any other recipients of the Work or
+          Derivative Works a copy of this License; and
+
+      (b) You must cause any modified files to carry prominent notices
+          stating that You changed the files; and
+
+      (c) You must retain, in the Source form of any Derivative Works
+          that You distribute, all copyright, patent, trademark, and
+          attribution notices from the Source form of the Work,
+          excluding those notices that do not pertain to any part of
+          the Derivative Works; and
+
+      (d) If the Work includes a "NOTICE" text file as part of its
+          distribution, then any Derivative Works that You distribute must
+          include a readable copy of the attribution notices contained
+          within such NOTICE file, excluding those notices that do not
+          pertain to any part of the Derivative Works, in at least one
+          of the following places: within a NOTICE text file distributed
+          as part of the Derivative Works; within the Source form or
+          documentation, if provided along with the Derivative Works; or,
+          within a display generated by the Derivative Works, if and
+          wherever such third-party notices normally appear. The contents
+          of the NOTICE file are for informational purposes only and
+          do not modify the License. You may add Your own attribution
+          notices within Derivative Works that You distribute, alongside
+          or as an addendum to the NOTICE text from the Work, provided
+          that such additional attribution notices cannot be construed
+          as modifying the License.
+
+      You may add Your own copyright statement to Your modifications and
+      may provide additional or different license terms and conditions
+      for use, reproduction, or distribution of Your modifications, or
+      for any such Derivative Works as a whole, provided Your use,
+      reproduction, and distribution of the Work otherwise complies with
+      the conditions stated in this License.
+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
+      Notwithstanding the above, nothing herein shall supersede or modify
+      the terms of any separate license agreement you may have executed
+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
+      names, trademarks, service marks, or product names of the Licensor,
+      except as required for reasonable and customary use in describing the
+      origin of the Work and reproducing the content of the NOTICE file.
+
+   7. Disclaimer of Warranty. Unless required by applicable law or
+      agreed to in writing, Licensor provides the Work (and each
+      Contributor provides its Contributions) on an "AS IS" BASIS,
+      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+      implied, including, without limitation, any warranties or conditions
+      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+      PARTICULAR PURPOSE. You are solely responsible for determining the
+      appropriateness of using or redistributing the Work and assume any
+      risks associated with Your exercise of permissions under this License.
+
+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
+      negligent acts) or agreed to in writing, shall any Contributor be
+      liable to You for damages, including any direct, indirect, special,
+      incidental, or consequential damages of any character arising as a
+      result of this License or out of the use or inability to use the
+      Work (including but not limited to damages for loss of goodwill,
+      work stoppage, computer failure or malfunction, or any and all
+      other commercial damages or losses), even if such Contributor
+      has been advised of the possibility of such damages.
+
+   9. Accepting Warranty or Additional Liability. While redistributing
+      the Work or Derivative Works thereof, You may choose to offer,
+      and charge a fee for, acceptance of support, warranty, indemnity,
+      or other liability obligations and/or rights consistent with this
+      License. However, in accepting such obligations, You may act only
+      on Your own behalf and on Your sole responsibility, not on behalf
+      of any other Contributor, and only if You agree to indemnify,
+      defend, and hold each Contributor harmless for any liability
+      incurred by, or claims asserted against, such Contributor by reason
+      of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright [yyyy] [name of copyright owner]
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.

licenses/CC-BY-4.0.txt

@@ -0,0 +1,156 @@
+Creative Commons Attribution 4.0 International
+
+ Creative Commons Corporation (“Creative Commons”) is not a law firm and does not provide legal services or legal advice. Distribution of Creative Commons public licenses does not create a lawyer-client or other relationship. Creative Commons makes its licenses and related information available on an “as-is” basis. Creative Commons gives no warranties regarding its licenses, any material licensed under their terms and conditions, or any related information. Creative Commons disclaims all liability for damages resulting from their use to the fullest extent possible.
+
+Using Creative Commons Public Licenses
+
+Creative Commons public licenses provide a standard set of terms and conditions that creators and other rights holders may use to share original works of authorship and other material subject to copyright and certain other rights specified in the public license below. The following considerations are for informational purposes only, are not exhaustive, and do not form part of our licenses.
+
+Considerations for licensors: Our public licenses are intended for use by those authorized to give the public permission to use material in ways otherwise restricted by copyright and certain other rights. Our licenses are irrevocable. Licensors should read and understand the terms and conditions of the license they choose before applying it. Licensors should also secure all rights necessary before applying our licenses so that the public can reuse the material as expected. Licensors should clearly mark any material not subject to the license. This includes other CC-licensed material, or material used under an exception or limitation to copyright. More considerations for licensors.
+
+Considerations for the public: By using one of our public licenses, a licensor grants the public permission to use the licensed material under specified terms and conditions. If the licensor’s permission is not necessary for any reason–for example, because of any applicable exception or limitation to copyright–then that use is not regulated by the license. Our licenses grant only permissions under copyright and certain other rights that a licensor has authority to grant. Use of the licensed material may still be restricted for other reasons, including because others have copyright or other rights in the material. A licensor may make special requests, such as asking that all changes be marked or described. Although not required by our licenses, you are encouraged to respect those requests where reasonable. More considerations for the public.
+
+Creative Commons Attribution 4.0 International Public License
+
+By exercising the Licensed Rights (defined below), You accept and agree to be bound by the terms and conditions of this Creative Commons Attribution 4.0 International Public License ("Public License"). To the extent this Public License may be interpreted as a contract, You are granted the Licensed Rights in consideration of Your acceptance of these terms and conditions, and the Licensor grants You such rights in consideration of benefits the Licensor receives from making the Licensed Material available under these terms and conditions.
+
+Section 1 – Definitions.
+
+     a.	Adapted Material means material subject to Copyright and Similar Rights that is derived from or based upon the Licensed Material and in which the Licensed Material is translated, altered, arranged, transformed, or otherwise modified in a manner requiring permission under the Copyright and Similar Rights held by the Licensor. For purposes of this Public License, where the Licensed Material is a musical work, performance, or sound recording, Adapted Material is always produced where the Licensed Material is synched in timed relation with a moving image.
+
+     b.	Adapter's License means the license You apply to Your Copyright and Similar Rights in Your contributions to Adapted Material in accordance with the terms and conditions of this Public License.
+
+     c.	Copyright and Similar Rights means copyright and/or similar rights closely related to copyright including, without limitation, performance, broadcast, sound recording, and Sui Generis Database Rights, without regard to how the rights are labeled or categorized. For purposes of this Public License, the rights specified in Section 2(b)(1)-(2) are not Copyright and Similar Rights.
+
+     d.	Effective Technological Measures means those measures that, in the absence of proper authority, may not be circumvented under laws fulfilling obligations under Article 11 of the WIPO Copyright Treaty adopted on December 20, 1996, and/or similar international agreements.
+
+     e.	Exceptions and Limitations means fair use, fair dealing, and/or any other exception or limitation to Copyright and Similar Rights that applies to Your use of the Licensed Material.
+
+     f.	Licensed Material means the artistic or literary work, database, or other material to which the Licensor applied this Public License.
+
+     g.	Licensed Rights means the rights granted to You subject to the terms and conditions of this Public License, which are limited to all Copyright and Similar Rights that apply to Your use of the Licensed Material and that the Licensor has authority to license.
+
+     h.	Licensor means the individual(s) or entity(ies) granting rights under this Public License.
+
+     i.	Share means to provide material to the public by any means or process that requires permission under the Licensed Rights, such as reproduction, public display, public performance, distribution, dissemination, communication, or importation, and to make material available to the public including in ways that members of the public may access the material from a place and at a time individually chosen by them.
+
+     j.	Sui Generis Database Rights means rights other than copyright resulting from Directive 96/9/EC of the European Parliament and of the Council of 11 March 1996 on the legal protection of databases, as amended and/or succeeded, as well as other essentially equivalent rights anywhere in the world.
+
+     k.	You means the individual or entity exercising the Licensed Rights under this Public License. Your has a corresponding meaning.
+
+Section 2 – Scope.
+
+     a.	License grant.
+
+          1. Subject to the terms and conditions of this Public License, the Licensor hereby grants You a worldwide, royalty-free, non-sublicensable, non-exclusive, irrevocable license to exercise the Licensed Rights in the Licensed Material to:
+
+               A. reproduce and Share the Licensed Material, in whole or in part; and
+
+               B. produce, reproduce, and Share Adapted Material.
+
+          2. Exceptions and Limitations. For the avoidance of doubt, where Exceptions and Limitations apply to Your use, this Public License does not apply, and You do not need to comply with its terms and conditions.
+
+          3. Term. The term of this Public License is specified in Section 6(a).
+
+          4. Media and formats; technical modifications allowed. The Licensor authorizes You to exercise the Licensed Rights in all media and formats whether now known or hereafter created, and to make technical modifications necessary to do so. The Licensor waives and/or agrees not to assert any right or authority to forbid You from making technical modifications necessary to exercise the Licensed Rights, including technical modifications necessary to circumvent Effective Technological Measures. For purposes of this Public License, simply making modifications authorized by this Section 2(a)(4) never produces Adapted Material.
+
+          5. Downstream recipients.
+
+               A. Offer from the Licensor – Licensed Material. Every recipient of the Licensed Material automatically receives an offer from the Licensor to exercise the Licensed Rights under the terms and conditions of this Public License.
+
+               B. No downstream restrictions. You may not offer or impose any additional or different terms or conditions on, or apply any Effective Technological Measures to, the Licensed Material if doing so restricts exercise of the Licensed Rights by any recipient of the Licensed Material.
+
+          6.  No endorsement. Nothing in this Public License constitutes or may be construed as permission to assert or imply that You are, or that Your use of the Licensed Material is, connected with, or sponsored, endorsed, or granted official status by, the Licensor or others designated to receive attribution as provided in Section 3(a)(1)(A)(i).
+
+b. Other rights.
+
+          1. Moral rights, such as the right of integrity, are not licensed under this Public License, nor are publicity, privacy, and/or other similar personality rights; however, to the extent possible, the Licensor waives and/or agrees not to assert any such rights held by the Licensor to the limited extent necessary to allow You to exercise the Licensed Rights, but not otherwise.
+
+          2. Patent and trademark rights are not licensed under this Public License.
+
+          3. To the extent possible, the Licensor waives any right to collect royalties from You for the exercise of the Licensed Rights, whether directly or through a collecting society under any voluntary or waivable statutory or compulsory licensing scheme. In all other cases the Licensor expressly reserves any right to collect such royalties.
+
+Section 3 – License Conditions.
+
+Your exercise of the Licensed Rights is expressly made subject to the following conditions.
+
+     a.	Attribution.
+
+          1. If You Share the Licensed Material (including in modified form), You must:
+
+               A. retain the following if it is supplied by the Licensor with the Licensed Material:
+
+                    i. identification of the creator(s) of the Licensed Material and any others designated to receive attribution, in any reasonable manner requested by the Licensor (including by pseudonym if designated);
+
+                    ii. a copyright notice;
+
+                    iii. a notice that refers to this Public License;
+
+                    iv.	a notice that refers to the disclaimer of warranties;
+
+                    v. a URI or hyperlink to the Licensed Material to the extent reasonably practicable;
+
+               B. indicate if You modified the Licensed Material and retain an indication of any previous modifications; and
+
+               C. indicate the Licensed Material is licensed under this Public License, and include the text of, or the URI or hyperlink to, this Public License.
+
+          2. You may satisfy the conditions in Section 3(a)(1) in any reasonable manner based on the medium, means, and context in which You Share the Licensed Material. For example, it may be reasonable to satisfy the conditions by providing a URI or hyperlink to a resource that includes the required information.
+
+          3. If requested by the Licensor, You must remove any of the information required by Section 3(a)(1)(A) to the extent reasonably practicable.
+
+          4. If You Share Adapted Material You produce, the Adapter's License You apply must not prevent recipients of the Adapted Material from complying with this Public License.
+
+Section 4 – Sui Generis Database Rights.
+
+Where the Licensed Rights include Sui Generis Database Rights that apply to Your use of the Licensed Material:
+
+     a.	for the avoidance of doubt, Section 2(a)(1) grants You the right to extract, reuse, reproduce, and Share all or a substantial portion of the contents of the database;
+
+     b.	if You include all or a substantial portion of the database contents in a database in which You have Sui Generis Database Rights, then the database in which You have Sui Generis Database Rights (but not its individual contents) is Adapted Material; and
+
+     c.	You must comply with the conditions in Section 3(a) if You Share all or a substantial portion of the contents of the database.
+For the avoidance of doubt, this Section 4 supplements and does not replace Your obligations under this Public License where the Licensed Rights include other Copyright and Similar Rights.
+
+Section 5 – Disclaimer of Warranties and Limitation of Liability.
+
+     a.	Unless otherwise separately undertaken by the Licensor, to the extent possible, the Licensor offers the Licensed Material as-is and as-available, and makes no representations or warranties of any kind concerning the Licensed Material, whether express, implied, statutory, or other. This includes, without limitation, warranties of title, merchantability, fitness for a particular purpose, non-infringement, absence of latent or other defects, accuracy, or the presence or absence of errors, whether or not known or discoverable. Where disclaimers of warranties are not allowed in full or in part, this disclaimer may not apply to You.
+
+     b.	To the extent possible, in no event will the Licensor be liable to You on any legal theory (including, without limitation, negligence) or otherwise for any direct, special, indirect, incidental, consequential, punitive, exemplary, or other losses, costs, expenses, or damages arising out of this Public License or use of the Licensed Material, even if the Licensor has been advised of the possibility of such losses, costs, expenses, or damages. Where a limitation of liability is not allowed in full or in part, this limitation may not apply to You.
+
+     c.	The disclaimer of warranties and limitation of liability provided above shall be interpreted in a manner that, to the extent possible, most closely approximates an absolute disclaimer and waiver of all liability.
+
+Section 6 – Term and Termination.
+
+     a.	This Public License applies for the term of the Copyright and Similar Rights licensed here. However, if You fail to comply with this Public License, then Your rights under this Public License terminate automatically.
+
+     b.	Where Your right to use the Licensed Material has terminated under Section 6(a), it reinstates:
+
+          1. automatically as of the date the violation is cured, provided it is cured within 30 days of Your discovery of the violation; or
+
+          2. upon express reinstatement by the Licensor.
+
+     c.	For the avoidance of doubt, this Section 6(b) does not affect any right the Licensor may have to seek remedies for Your violations of this Public License.
+
+     d.	For the avoidance of doubt, the Licensor may also offer the Licensed Material under separate terms or conditions or stop distributing the Licensed Material at any time; however, doing so will not terminate this Public License.
+
+     e.	Sections 1, 5, 6, 7, and 8 survive termination of this Public License.
+
+Section 7 – Other Terms and Conditions.
+
+     a.	The Licensor shall not be bound by any additional or different terms or conditions communicated by You unless expressly agreed.
+
+     b.	Any arrangements, understandings, or agreements regarding the Licensed Material not stated herein are separate from and independent of the terms and conditions of this Public License.
+
+Section 8 – Interpretation.
+
+     a.	For the avoidance of doubt, this Public License does not, and shall not be interpreted to, reduce, limit, restrict, or impose conditions on any use of the Licensed Material that could lawfully be made without permission under this Public License.
+
+     b.	To the extent possible, if any provision of this Public License is deemed unenforceable, it shall be automatically reformed to the minimum extent necessary to make it enforceable. If the provision cannot be reformed, it shall be severed from this Public License without affecting the enforceability of the remaining terms and conditions.
+
+     c.	No term or condition of this Public License will be waived and no failure to comply consented to unless expressly agreed to by the Licensor.
+
+     d.	Nothing in this Public License constitutes or may be interpreted as a limitation upon, or waiver of, any privileges and immunities that apply to the Licensor or You, including from the legal processes of any jurisdiction or authority.
+
+Creative Commons is not a party to its public licenses. Notwithstanding, Creative Commons may elect to apply one of its public licenses to material it publishes and in those instances will be considered the “Licensor.” Except for the limited purpose of indicating that material is shared under a Creative Commons public license or as otherwise permitted by the Creative Commons policies published at creativecommons.org/policies, Creative Commons does not authorize the use of the trademark “Creative Commons” or any other trademark or logo of Creative Commons without its prior written consent including, without limitation, in connection with any unauthorized modifications to any of its public licenses or any other arrangements, understandings, or agreements concerning use of licensed material. For the avoidance of doubt, this paragraph does not form part of the public licenses.
+
+Creative Commons may be contacted at creativecommons.org.

manifest.json

@@ -0,0 +1,148 @@
+{
+  "schema_version": 1,
+  "release": "v1.0.0",
+  "repo_id": "anushkrishna/falcon-models",
+  "documentation": [
+    "README.md",
+    "LICENSE.md",
+    "licenses/Apache-2.0.txt",
+    "licenses/CC-BY-4.0.txt",
+    "sources/allam-README.md",
+    "sources/marian-en-ar-README.md",
+    "sources/marian-ar-en-README.md"
+  ],
+  "packs": [
+    {
+      "id": "allam-q4-k-m",
+      "upstream_repo": "humain-ai/ALLaM-7B-Instruct-preview",
+      "upstream_revision": "a28dd1e67420cde72d3629c8633a974cf7d9c366",
+      "license": "apache-2.0",
+      "runtime": "llama.cpp",
+      "format": "gguf",
+      "quantization": "Q4_K_M",
+      "conversion_tool_revision": "58367713a6935c0810103378144008df32e3d5db",
+      "chat_template_sha256": "f1dff938141b507da4a409b6bb3431382088a97a963acd246a41f2f344ae831f",
+      "files": [
+        {
+          "path": "allam/allam-7b-instruct-preview-Q4_K_M.gguf",
+          "byte_size": 4263194080,
+          "sha256": "e71791258a787ebe5d14c4bb01b7403d6390ada51e50e146899fae6db965cdc2"
+        },
+        {
+          "path": "allam/tokenizer.model",
+          "byte_size": 1228714,
+          "sha256": "feff3deb3537c4a47b77585053ad2aa00484da7907b188e0111cbed1f4592e67"
+        },
+        {
+          "path": "allam/tokenizer_config.json",
+          "byte_size": 1620,
+          "sha256": "37bcb27b4b135353488e79314ceb16182049265c95790e6586b2afeb62e40093"
+        },
+        {
+          "path": "allam/config.json",
+          "byte_size": 686,
+          "sha256": "77494ef4de9d6450f94d566f5ccc63aedbcf6944b57ceedc6677f94cc315086d"
+        }
+      ]
+    },
+    {
+      "id": "marian-en-ar-int8",
+      "upstream_repo": "Helsinki-NLP/opus-mt-tc-big-en-ar",
+      "upstream_revision": "ae9f1b2fd512000ca9440eb3b8ec9aa9acb298ac",
+      "license": "cc-by-4.0",
+      "runtime": "CTranslate2",
+      "format": "ctranslate2",
+      "quantization": "int8",
+      "conversion_tool_version": null,
+      "conversion_note": "Exact converter environment not recorded for these existing artifacts; identify them by hashes. Use scripts/convert-marian-models.sh for future conversions with a recorded, pinned toolchain.",
+      "files": [
+        {
+          "path": "marian/en-ar/config.json",
+          "byte_size": 223,
+          "sha256": "8f6496adfc930cbfecbe8281112197705c488fab47d34b4829b06d7f478909af"
+        },
+        {
+          "path": "marian/en-ar/model.bin",
+          "byte_size": 242290503,
+          "sha256": "1c3482bdf098be1a8bfb6242093964a585d668c3f96c60883d761cd43730b9d8"
+        },
+        {
+          "path": "marian/en-ar/shared_vocabulary.json",
+          "byte_size": 1787481,
+          "sha256": "a0e6bb37588d1134dd47116c74674e49a809a8e6cecdeb5782f1b8956cb058e3"
+        },
+        {
+          "path": "marian/en-ar/source.spm",
+          "byte_size": 806127,
+          "sha256": "0a9b220e324e29d4fbab530747ab82968a79d5408f1b3210f0f6d812d148b7d2"
+        },
+        {
+          "path": "marian/en-ar/target.spm",
+          "byte_size": 916373,
+          "sha256": "db09c46631638384f2b13ccdececb1c88103f0e59c14d5def247975007e7eaac"
+        }
+      ]
+    },
+    {
+      "id": "marian-ar-en-int8",
+      "upstream_repo": "Helsinki-NLP/opus-mt-tc-big-ar-en",
+      "upstream_revision": "bcb4acd39ee8e3552e171653a8e31a10729b4330",
+      "license": "cc-by-4.0",
+      "runtime": "CTranslate2",
+      "format": "ctranslate2",
+      "quantization": "int8",
+      "conversion_tool_version": null,
+      "conversion_note": "Exact converter environment not recorded for these existing artifacts; identify them by hashes. Use scripts/convert-marian-models.sh for future conversions with a recorded, pinned toolchain.",
+      "files": [
+        {
+          "path": "marian/ar-en/config.json",
+          "byte_size": 223,
+          "sha256": "8f6496adfc930cbfecbe8281112197705c488fab47d34b4829b06d7f478909af"
+        },
+        {
+          "path": "marian/ar-en/model.bin",
+          "byte_size": 242148363,
+          "sha256": "c9d1c328668df8f2e620ace15ceb522be5b699f698d29e33e20e53b9677cb53f"
+        },
+        {
+          "path": "marian/ar-en/shared_vocabulary.json",
+          "byte_size": 1779312,
+          "sha256": "44d71ff9b75b066d1b56c7d87cd52258603269fdde99e8b02c47a7b9bdc5852e"
+        },
+        {
+          "path": "marian/ar-en/source.spm",
+          "byte_size": 915066,
+          "sha256": "fce8e7e41d2e9337d5176edc530bd900efd6d99f86153f755c88529796b67a65"
+        },
+        {
+          "path": "marian/ar-en/target.spm",
+          "byte_size": 804240,
+          "sha256": "cd90eef39e9f181bac516565a7bfc239306ecd446eb0adc85a44be4458fe6fe9"
+        }
+      ]
+    }
+  ],
+  "external_artifacts": [
+    {
+      "id": "paddleocr-det_small.onnx",
+      "url": "https://huggingface.co/PaddlePaddle/PP-OCRv6_small_det_onnx/resolve/28fe5895c24fd108c19eb3e8479f4ab385fbfc62/inference.onnx?download=true",
+      "byte_size": 9880512,
+      "sha256": "d73e0058b7a8086bbd57f3d10b8bcd4ff95363f67e06e2762b5e814fe9c9410e",
+      "mirrored": false
+    },
+    {
+      "id": "paddleocr-rec_en_mobile.onnx",
+      "url": "https://huggingface.co/PaddlePaddle/en_PP-OCRv5_mobile_rec_onnx/resolve/3fafbc3b5dcf93dd72add9f48368be8a3a2cd33b/inference.onnx?download=true",
+      "byte_size": 7848423,
+      "sha256": "b5f833dfc5d0eb71da397b4efa06ebeee9b431b690a47d6af40d77d8eabc557f",
+      "mirrored": false
+    },
+    {
+      "id": "paddleocr-rec_ar_mobile.onnx",
+      "url": "https://huggingface.co/PaddlePaddle/arabic_PP-OCRv5_mobile_rec_onnx/resolve/14aaedcd75825982689ecf5cd64ab33ee083215a/inference.onnx?download=true",
+      "byte_size": 7998947,
+      "sha256": "799113ebf267fbe742deb99eb36e8d42c9ddc5291ceacf92add41b4d52a59110",
+      "mirrored": false
+    }
+  ]
+}

marian/ar-en/config.json

@@ -0,0 +1,10 @@
+{
+  "add_source_bos": false,
+  "add_source_eos": false,
+  "bos_token": "<s>",
+  "decoder_start_token": "</s>",
+  "eos_token": "</s>",
+  "layer_norm_epsilon": null,
+  "multi_query_attention": false,
+  "unk_token": "<unk>"
+}

marian/ar-en/model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c9d1c328668df8f2e620ace15ceb522be5b699f698d29e33e20e53b9677cb53f
+size 242148363

marian/ar-en/source.spm

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fce8e7e41d2e9337d5176edc530bd900efd6d99f86153f755c88529796b67a65
+size 915066

marian/ar-en/target.spm

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cd90eef39e9f181bac516565a7bfc239306ecd446eb0adc85a44be4458fe6fe9
+size 804240

marian/en-ar/config.json

@@ -0,0 +1,10 @@
+{
+  "add_source_bos": false,
+  "add_source_eos": false,
+  "bos_token": "<s>",
+  "decoder_start_token": "</s>",
+  "eos_token": "</s>",
+  "layer_norm_epsilon": null,
+  "multi_query_attention": false,
+  "unk_token": "<unk>"
+}

marian/en-ar/model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1c3482bdf098be1a8bfb6242093964a585d668c3f96c60883d761cd43730b9d8
+size 242290503

marian/en-ar/source.spm

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0a9b220e324e29d4fbab530747ab82968a79d5408f1b3210f0f6d812d148b7d2
+size 806127

marian/en-ar/target.spm

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:db09c46631638384f2b13ccdececb1c88103f0e59c14d5def247975007e7eaac
+size 916373

sources/allam-README.md

@@ -0,0 +1,241 @@
+---
+license: apache-2.0
+language:
+- ar
+- en
+pipeline_tag: text-generation
+tags:
+  - pytorch
+library_name: transformers
+---
+# ALLaM-7B-Instruct-preview 
+
+ALLaM is a series of powerful language models designed to advance Arabic Language Technology (ALT) developed by the National Center for Artificial Intelligence (NCAI) at the [Saudi Data and AI Authority (SDAIA)](https://sdaia.gov.sa/en/default.aspx). `ALLaM-AI/ALLaM-7B-Instruct-preview` is trained from scratch. Our pretraining from scratch recipe consists of two steps: training on 4T English tokens followed by training on 1.2T mixed Arabic/English tokens. This retains the English capabilities of the model without catastrophic forgetting, effectively transferring knowledge from one language distribution to another.
+
+## Intended Use
+
+`ALLaM` is specifically designed to expedite the research and development of ALT through Large Language Models (LLM). It serves as one of the foundational elements for building product offerings as well as facilitating experimental initiatives. 
+
+The ALLaM series models are designed to be a component of a larger AI system, and it is important for developers to incorporate safety measures when creating these systems. These safety measures are crucial for ensuring a balance between effectiveness and security, as well as minimizing potential risks, such as those resulting from the integration of the model with external tools.
+
+## Model Details
+
+ALLaM is a family of LLMs specially trained for Arabic. The main two paths followed for pretraining are: 
+
+- **ALLaM**: Pretraining models from scratch
+- **ALLaM-Adapted/ALLaM-(\*\*)/(\*\*)-ALLaM**/: Continued training from open source/weight models
+
+For this release, we are providing our instruction-tuned 7B parameter generative model pretrained from scratch.
+
+Some parameters for this model are provided in the following table: 
+
+| Size           | Context Length  | Pretraining Tokens | Instructions | Preference Pairs |
+|----------------|-----------------|--------------------|--------------|------------------|
+| 7B parameters  | 4096 tokens     |4T(en) + 1.2T(en+ar)| 7M           | 260K             |
+
+#### Model Revisions Loading Tags:
+
+- **Version 7b-alpha-v1.27.2.25 (Old Release)**: `revision = "v1"`
+- **Version 7b-alpha-v2.33.0.30 (Newest Releas)**: `revision = "v2"`
+
+## Model Description
+
+- **Developed by:** National Center for Artificial Intelligence at [SDAIA](https://sdaia.gov.sa/en/default.aspx)
+- **Model type:** Autoregressive Transformer
+- **Language(s):** Arabic, English
+- **License:** Please see the LICENSE file
+- **Input:** Text
+- **Output:** Text
+
+
+## Training Details 
+
+ALLaM-7B-Instruct-preview  is pretrained on a total of 5.2 trillion tokens in English and Arabic, Our training codebase is built on [NVIDIA/MegatronLM](https://github.com/NVIDIA/Megatron-LM). Average MFU during training was ~42%. We trained our model using bf16-mixed precision.
+
+
+## Getting started
+
+
+### System Prompt
+
+It is important to note that this model is optimized to function without a predefined system prompt.
+While Allam does not come with a default system prompt, it does provide the flexibility to add a custom system prompt.
+For instance, a well crafted system prompt could be:
+
+“You are ALLaM, a bilingual English and Arabic AI assistant.”
+System prompts can also be in Arabic:
+
+"أنت علام، مساعد ذكاء اصطناعي مطور من الهيئة السعودية للبيانات والذكاء الاصطناعي، تجيب على الأسئلة بطريقة مفيدة مع مراعاة القيم الثقافية المحلية."
+Alternatively, users can get creative with their prompts, such as:
+
+“You are an AI assistant who responds to everything like a pirate.”
+
+The system prompt is integrated inside the tokenizer config (accessed via `apply_chat_template()` module). 
+
+
+### Example Usages
+
+The weights for ALLaM model checkpoints can be accessed via [HuggingFace transformers](https://github.com/huggingface/transformers) (tested with `transformers>=4.40.1`). The following code snippet demonstrates how to load the model and generate text using the `ALLaM-AI/ALLaM-7B-Instruct-preview` model.
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+allam_model = AutoModelForCausalLM.from_pretrained("ALLaM-AI/ALLaM-7B-Instruct-preview") 
+tokenizer = AutoTokenizer.from_pretrained("ALLaM-AI/ALLaM-7B-Instruct-preview") 
+messages=[
+    {"role": "user", "content": "كيف أجهز كوب شاهي؟"},
+]
+inputs = tokenizer.apply_chat_template(messages, tokenize=False)
+inputs = tokenizer(inputs, return_tensors='pt', return_token_type_ids=False)
+inputs = {k: v.to('cuda') for k,v in inputs.items()}
+allam_model = allam_model.to('cuda')
+response = allam_model.generate(**inputs, max_new_tokens=4096, do_sample=True, top_k=50, top_p=0.95, temperature=.6)
+print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
+```
+
+
+## Ethical Considerations and Limitations
+
+ALLaM is a generative model that comes with inherent uncertainties. Trials cannot encompass every possible use case. Hence, predicting ALLaM's responses in every context is not possible, leading on occasion to incorrect or biased outputs. Developers must conduct thorough safety evaluations and make specific adjustments to ensure the model is suitable for the intended purposes. 
+
+*The output generated by this model is not considered a statement of NCAI, SDAIA, or any other organization.*
+
+## Evaluation
+
+### Automatic Benchmarks
+
+#### Arabic Benchmarks
+**Massive Multitask Language Understanding** (MMLU) is a collection of many multiple-choice evaluation questions sourced from various academic levels (elementary to college level). These questions are typically related to humanities, STEM, or social sciences. It was originally an English dataset, but other variants were developed for Arabic: 
+
+<!-- - [Original English MMLU (MMLU-en)](https://github.com/hendrycks/test): A collection of 14,079 original English questions spanning 57 domains.  -->
+- [Arabic MMLU](https://huggingface.co/datasets/MBZUAI/ArabicMMLU): A collection of 14,575 original Arabic questions spanning 40 domains published by MBZUAI. 
+- [OpenAI MMLU-ar](https://huggingface.co/datasets/openai/MMMLU): A dataset comprising 14,042 questions, translated from the original MMLU benchmark published by OpenAI.
+
+**Exams Arabic** ([Exams (Ar)](https://github.com/FreedomIntelligence/Arabic-eval/blob/main/LLM/benchmark_eval/benchmarks/EXAMS_Arabic/exam_test.jsonl)): A multiple choice question dataset with 537 samples, covering several domains e.g., Islamic studies, science, humanities, and physics. 
+
+**Arabic Cultural Alignment** ([ACVA](https://huggingface.co/datasets/FreedomIntelligence/ACVA-Arabic-Cultural-Value-Alignment)): This dataset was generated by `gpt-3.5-turbo` and contains 8,710 True and False questions from 58 different areas.
+
+**Education and Training Evaluation Commission** (ETEC): This dataset consists of Arabic-language multiple-choice questions, compiled by the ALLaM team in collaboration with [Saudi ETEC](https://acpd.etec.gov.sa/Home/index?csrt=5175167507218838843). It spans various educational levels, from elementary through post-college, with a total of 1,887  test samples. 
+
+**IEN**: This dataset was curated from the Ministry of Education's (MOE) [IEN platform](https://www.ientv.edu.sa/ar), organized by grade, topic, and difficulty level. It comprehensively covers the entire Saudi curriculum from 1st grade through high school, with 9990 multiple-choice questions and 5823 true/false questions.
+
+**GAT**: The General Aptitude Test (GAT) dataset consists of approximately 16,000 Arabic multiple-choice questions, representing various sections of [the Qiyas General Aptitude Test](https://www.etec.gov.sa/en/service/Generalabilitytest/servicegoal). The sections include algebra, reading comprehension, analogies, arithmetic, associations, comparisons, completions, contextual understanding, and geometry.
+
+**AraPro**: A curated collection of 5,001 multiple-choice questions (MCQs) authored by our domain experts. The dataset spans various subjects, including mathematics, science, and other relevant fields, providing a diverse set of questions for evaluation purpose.
+
+**AraMath**: AraMath consists of 605 MCQs derived from [ArMath](https://github.com/reem-codes/ArMATH), which includes mathematical word problems, that was transformed to MCQs internally. 
+
+**Ar-IFEval**: an Arabic instruction-following (IF) evaluation dataset designed to automatically assess language models' compliance with specified instructions through verifiable methods. The dataset consists of 535 instances, each containing two to four verifiable instructions that can be validated using deterministic programming approaches.
+
+All models were evaluated using our proprietary evaluation pipeline and [LM Evaluation Harness framework](https://github.com/EleutherAI/lm-evaluation-harness) to ensure fair comparisons. For API-based models, we used exact match evaluations of the generated outputs.
+
+The evaluation scores of ALLaM can be found in JSON format [here](https://huggingface.co/ALLaM-AI/ALLaM-7B-Instruct-preview/tree/main/evaluation). 
+
+
+| Model                       |AVG | ETEC <br>0 shot   | IEN-MCQ <br>0 shot   | IEN-TF <br>0 shot   | AraPro <br>0 shot   | AraMath <br>5 shot   | Ar-IFEval <br>(prompt strict) <br>0 shot   | Ar-IFEval <br>(inst strict) <br>0 shot   | ExamsAR <br>5 shot   | ACVA  <br> 5 shot   | Arabic MMLU <br>0 Shot   | Openai MMLU <br>0 shot   | GAT  <br>0 shot   | 
+|:----------------------------|:----------|:---------|:-----------------|:----------------|:----------------|:-----------------|:-----------------------------------|:---------------------------------|:------------------|:--------------|:--------------------|:--------------------|:-----------------------------|
+| ALLaM-7B-Instruct-preview   | 64.42     | 66.67    | **91.77**        | 82.95           | 69.71           | 66.78            | 31.34                              | 67.65                            | 51.58             | 76.33         | 67.78               | 55.91               | 44.53                        |
+| AceGPT-v2-8B-Chat           | 52.67     | 56.81    | 77.01            | 75.91           | 63.51           | 41.49            | 10.26                              | 39.25                            | 51.96             | 72.69         | 57.02               | 49.99               | 36.15                        |
+| AceGPT-v2-32B-Chat          | 62.23     | 64.81    | 81.6             | 80.35           | 67.19           | 64.46            | 25.75                              | 63.41                            | 55.31             | 71.57         | 68.3                | 60.8                | 43.21                        |
+| jais-family-6p7b-chat       | 46.31     | 45.47    | 46.22            | 63.92           | 54.31           | 25.29            | 13.99                              | 52.97                            | 46.93             | 73.8          | 56.15               | 44.96               | 31.71                        |
+| jais-family-13b-chat        | 49.14     | 48.65    | 62.95            | 68.68           | 57.53           | 26.61            | 17.16                              | 54.27                            | 45.07             | 71.18         | 58.14               | 47.73               | 31.72                        |
+| jais-family-30b-16k-chat    | 52.54     | 53.31    | 74.88            | 68.76           | 62.79           | 41.49            | 16.6                               | 54.95                            | 49.72             | 60.08         | 62.04               | 50.98               | 34.85                        |
+| jais-family-30b-8k-chat     | 53.19     | 53.52    | 72.76            | 70.65           | 61.27           | 33.39            | 16.79                              | 54.68                            | 50.28             | 74.47         | 63.11               | 50.9                | 36.44                        |
+| jais-adapted-7b-chat        | 45.19     | 40.49    | 57.38            | 67.18           | 50.59           | 28.43            | 14.93                              | 54.27                            | 40.6              | 70.44         | 49.75               | 38.54               | 29.68                        |
+| jais-adapted-13b-chat       | 51.86     | 48.12    | 69.65            | 71.85           | 59.07           | 37.02            | 23.32                              | 60.61                            | 48.23             | 67.78         | 56.42               | 46.83               | 33.4                         |
+| jais-adapted-70b-chat       | 58.32     | 56.81    | 74.51            | 76.47           | 64.59           | 45.62            | 27.05                              | 65.05                            | 54.75             | 73.33         | 65.74               | 56.82               | 39.15                        |
+| Qwen2.5-7B-Instruct         | 60.55     | 64.12    | 66.38            | 78.46           | 64.63           | 71.74            | 28.17                              | 65.19                            | 50.65             | 78.17         | 61.54               | 56.1                | 41.42                        |
+| Qwen2.5-14B-Instruct        | 71.26     | 72.18    | 80.51            | 77.64           | 69.11           | 82.81            | 68.66                              | 86.76                            | 57.54             | 75.04         | 69.36               | 63.8                | 51.7                         |
+| Qwen2.5-72B-Instruct        | **76.91** | **78.7** | 86.88            | **86.62**       | **74.69**       | **92.89**        | 67.72                              | 87.51                            | 60.71             | **79.92**     | **74.1**            | **73.59**           | **59.54**                    |
+| Mistral-7B-Instruct-v0.3    | 43.05     | 35.67    | 53.59            | 63.4            | 43.85           | 27.11            | 30.41                              | 64.03                            | 34.08             | 60.25         | 45.27               | 32.3                | 26.65                        |
+| Mistral-Nemo-Instruct-2407  | 53.79     | 49.28    | 68.43            | 71.78           | 57.61           | 40.0             | 35.82                              | 70.58                            | 47.49             | 76.92         | 55.97               | 46.15               | 25.44                        |
+| Mistral-Small-Instruct-2409 | 51.11     | 40.96    | 60.64            | 63.66           | 47.73           | 44.46            | 51.12                              | 78.16                            | 38.73             | 68.93         | 50.43               | 39.63               | 28.82                        |
+| Falcon3-7B-Instruct         | 41.3      | 37.52    | 52.65            | 57.63           | 41.47           | 56.53            | 8.58                               | 47.92                            | 31.84             | 58.98         | 42.08               | 32.36               | 27.99                        |
+| Meta-Llama-3.1-8B-Instruct  | 54.08     | 45.68    | 59.23            | 71.7            | 52.51           | 34.38            | 51.87                              | 79.11                            | 52.51             | 69.93         | 56.43               | 44.67               | 30.9                         |
+| Llama-3.3-70B-Instruct      | 71.43     | 68.84    | 79.6             | 78.81           | 70.49           | 70.91            | **70.9**                           | **88.6**                         | **65.74**         | 76.93         | 72.01               | 70.25               | 44.12                        |
+
+Closed models evaluations:
+
+| Model                                  | ETEC <br>0 shot   | IEN-MCQ <br>0 shot   | IEN-TF <br>0 shot   | AraPro <br>0 shot   | AraMath <br>5 shot   | ARIFEval <br>(prompt strict) <br>0 shot   | ARIFEval <br>(inst strict) <br>0 shot   | ExamsAR <br>5 shot   | ACVA  <br> 5 shot   | Arabicmmlu <br>0 Shot   | Openai mmlu <br>0 shot   | GAT 0 shot   |
+|:---------------------------------------|:--------------|:-----------------|:----------------|:----------------|:-----------------|:----------------------------------|:--------------------------------|:-----------------|:-----------------------|:--------------------|:---------------------|:----------------------|
+| Azureml GPT4o (gpt-4o-900ptu)   | 79.39         | **92.03**        | 88.97           | 80.86           | 83.47            | 70.9                              | 88.12                           | 61.82            | 72.51                  | 79.02               | **76.5**             | 62.65                 |
+| Claude Sonnet 3.5 (claude-3-5-sonnet-20241022) | **85.9**      | 86.17            | **89.42**       | **81.46**       | 79.83            | 53.73                             | 80.14                           | **62.38**        | **80.42**              | 69.5                | 66.4                 | **68.89**             |
+| gemini pro 1.5 (gemini-1.5-pro)          | 83.31         | 88.28            | 85.44           | 76.22           | **94.88**        | **74.81**                         | **90.17**                       | 58.1             | 75.17                  | **82.0**            | 64.8                 | 59.14                 |
+
+#### English Benchmarks
+
+| model                             |Avg        | AGIEval 0 Shot |   Arc (challenge) 0 Shot |   GPQA (main) 0 Shot |   Hendrycks <br>ethics 0 Shot |   Winogrande 0 Shot |   HellaSwag 0 Shot |   TriviaQa 5 Shot |   MMLU Pro<br>5 Shot |   Minerva Math <br>4 Shot |   MMLU 0 Shot |   TruthfulQA <br>(mc2) 0 Shot |   IFEval <br>(prompt strict)<br>0 Shot |   IFEval <br>(inst strict)<br>0 Shot |   GSM8k 5 Shot |
+|:----------------------------------|:----------|:-----------------|:-----------------------|:--------------------------|:--------------------------|:--------------------|:-------------------|:------------------|:------------------|:----------------------|:--------------|:------------------------|:---------------------------------|:-------------------------------|:---------------|
+| ALLaM-7B-Instruct-preview         | 46.85     | 41.99            | 51.28                  | 22.77                     | 73.17                     | 70.48               | 76.26              | 16.07             | 30.4              | 17.3                  | 59.6          | 46.67                   | 38.08                            | 50.0                           | 61.79          |
+| AceGPT-v2-8B-Chat                 | 49.51     | 37.17            | 53.5                   | 25.67                     | 68.14                     | 73.72               | 79.21              | 67.65             | 37.38             | 17.58                 | 64.62         | 55.2                    | 23.48                            | 32.97                          | 56.86          |
+| AceGPT-v2-32B-Chat                | 57.14     | 56.01            | 53.92                  | 32.8125                   | 66.23                     | 79.16               | 83.29              | 69.45             | 45.89             | 32.8                  | 74.03         | 59.18                   | 27.54                            | 40.89                          | 78.7           |
+| jais-family-6p7b-chat             | 38.33     | 30.56            | 44.62                  | 23.21                     | 65.7                      | 62.43               | 72.05              | 29.74             | 23.3              | 2.56                  | 49.62         | 40.99                   | 14.05                            | 23.5                           | 54.36          |
+| jais-family-13b-chat              | 42.62     | 30.31            | 47.87                  | 25.89                     | 65.91                     | 65.04               | 75.0               | 35.82             | 24.4              | 19.1                  | 51.91         | 40.57                   | 19.41                            | 30.82                          | 64.59          |
+| jais-family-30b-16k-chat          | 45.15     | 31.85            | 48.46                  | 23.88                     | 69.44                     | 68.19               | 76.21              | 43.99             | 29.11             | 22.3                  | 58.5          | 44.78                   | 18.3                             | 29.14                          | 67.93          |
+| jais-family-30b-8k-chat           | 47.59     | 36.65            | 48.38                  | 21.88                     | 69.28                     | 70.32               | 78.55              | 46.67             | 28.7              | 26.44                 | 57.46         | 49.49                   | 22.92                            | 37.05                          | 72.48          |
+| jais-adapted-7b-chat              | 44.91     | 32.9             | 52.65                  | 23.88                     | 55.32                     | 71.74               | 79.39              | 63.89             | 24.38             | 15.34                 | 52.36         | 41.12                   | 22.0                             | 35.73                          | 58.07          |
+| jais-adapted-13b-chat             | 47.7      | 36.49            | 54.18                  | 26.34                     | 65.73                     | 69.77               | 80.86              | 58.48             | 26.29             | 21.34                 | 55.66         | 42.27                   | 24.95                            | 36.57                          | 68.84          |
+| jais-adapted-70b-chat             | 53.49     | 39.96            | 59.56                  | 20.98                     | 70.8                      | 77.27               | 84.06              | 68.64             | 37.25             | 27.72                 | 65.23         | 44.49                   | 31.61                            | 44.0                           | 77.26          |
+| Qwen2.5-7B-Instruct               | 54.68     | 59.2             | 51.28                  | 26.56                     | 73.76                     | 69.38               | 79.55              | 50.59             | 44.92             | 12.04                 | 70.56         | 58.93                   | 57.3                             | 68.23                          | 43.29          |
+| Qwen2.5-14B-Instruct              | 62.37     | 66.32            | 62.12                  | 25.89                     | 76.19                     | 75.77               | 84.36              | 59.47             | 52.44             | 23.04                 | 78.93         | 69.01                   | 52.13                            | 64.03                          | 83.47          |
+| Qwen2.5-72B-Instruct              | **70.06** | **71.09**        | **63.48**              | 25.67                     | 78.33                     | 76.24               | **87.41**          | 70.9              | **62.77**         | **54.04**             | **83.44**     | **69.54**               | 67.65                            | 77.1                           | **93.25**      |
+| Mistral-7B-Instruct-v0.3          | 51.98     | 36.45            | 58.87                  | 23.21                     | 72.58                     | 73.95               | 82.93              | 67.97             | 33.18             | 13.44                 | 59.74         | 59.69                   | 42.51                            | 54.8                           | 48.37          |
+| Mistral-Nemo-Instruct-2407        | 54.0      | 39.65            | 59.04                  | 24.33                     | 67.86                     | 74.66               | 82.35              | 72.77             | 44.27             | 29.62                 | 65.56         | 54.88                   | 30.13                            | 38.97                          | 71.95          |
+| Mistral-Small-Instruct-2409       | 61.65     | 40.76            | 60.49                  | 25.89                     | 72.27                     | 78.53               | 85.35              | 79.11             | 47.47             | 39.42                 | 69.42         | 56.35                   | 58.23                            | 68.35                          | 81.43          |
+| Falcon3-7B-Instruct               | 58.04     | 43.84            | 59.47                  | **33.71**                 | 70.39                     | 70.09               | 78.43              | 51.98             | 46.73             | 30.76                 | 68.14         | 55.53                   | 56.01                            | 68.59                          | 78.92          |
+| Meta-Llama-3.1-8B-Instruct        | 56.5      | 42.39            | 55.12                  | 27.23                     | 66.69                     | 73.95               | 79.28              | 70.05             | 40.641622         | 34.26                 | 67.96         | 54.05                   | 44.36                            | 58.51                          | 76.5           |
+| Llama-3.3-70B-Instruct            | 67.7      | 55.44            | 63.4                   | 25.89                     | **81.05**                 | **79.24**           | 84.39              | **81.7**              | 60.51             | 46.42                 | 81.99         | 60.91                   | **63.22**                           | **72.78**                          | 90.83          |
+
+### MT-bench
+
+**Multi-Turn Bench** (MT-Bench): A challenging multi-turn benchmark that uses GPT-4o as a judge. MT-bench comprises 80 questions from 8 domains. Each question is presented to the model and the responses are submitted to GPT-4o to assign scores to each response. The judge returns a score for the first and second turn separately.
+This dataset was also automatically translated to Arabic and manually verified and culturally aligned.
+
+| Model               | AR Average | AR Turn 1 | AR Turn 2 | EN Average | EN Turn 1 | EN Turn 2 |
+|---------------------|------------|-----------|-----------|------------|-----------|-----------|
+| ALLaM-7B-Instruct-preview     | 5.9 | **6.93**| 4.88 | 6.5 | 7.49 | 5.15 |
+| AceGPT-v1.5-13B-Chat   | 4.61 | 5.28 | 	3.93 | 4.86 | 5.56 | 4.17 |
+| AceGPT-v2-32B-Chat     |5.43 | 6.61 | 4.26 | **6.5** | **7.41** | **5.58** |
+| jais-family-13b-chat    | 4.89 | 5.37 | 4.41 | 4.77 | 5.57 | 3.97
+| jais-family-30b-16k-chat | 4.87 | 5.50 | 4.25  | 5.13  | 5.86 | 4.4  |
+| jais-adapted-70b-chat  | 5.86 | 6.33 | **5.38** | 5.88 | 6.41 | 5.36 |
+
+## Citation
+
+If you found this work helpful or used any part of this work, please include the following citation:
+
+```
+@inproceedings{
+    bari2025allam,
+    title={{ALL}aM: Large Language Models for Arabic and English},
+    author={M Saiful Bari and Yazeed Alnumay and Norah A. Alzahrani and Nouf M. Alotaibi and Hisham Abdullah Alyahya and Sultan AlRashed and Faisal Abdulrahman Mirza and Shaykhah Z. Alsubaie and Hassan A. Alahmed and Ghadah Alabduljabbar and Raghad Alkhathran and Yousef Almushayqih and Raneem Alnajim and Salman Alsubaihi and Maryam Al Mansour and Saad Amin Hassan and Dr. Majed Alrubaian and Ali Alammari and Zaki Alawami and Abdulmohsen Al-Thubaity and Ahmed Abdelali and Jeril Kuriakose and Abdalghani Abujabal and Nora Al-Twairesh and Areeb Alowisheq and Haidar Khan},
+    booktitle={The Thirteenth International Conference on Learning Representations},
+    year={2025},
+    url={https://openreview.net/forum?id=MscdsFVZrN}
+}
+```
+
+Apart from the authors of the paper, the ALLaM team is rapidly growing, supported by a large and talented group of in-house professionals, whom we gratefully acknowledge here.
+
+### Acknowledgment
+
+This release is funded by **Saudi Data & AI Authority**. We thank **Mishari Almishari** and **Yaser Alonaizan** for leading the **ALLaM** project. We list below the different teams that supported the development of **ALLaM**.
+
+#### Member of the Technical Staff:
+
+Alhanoof Althnian, Iman Albilali, Jubair Sheikh, Ibrahim Mammu, Ghadah Alsaif, Abdulhameed Alothaimeen, Hadeel Alnegheimish, Emad Alghamdi, Khalid Almubarak, Atheer Al-Barqi, Batool Al-Otaibi, Muhammad Al-Hajji, Abdulraouf Al-Maasoumi, Abdulmajeed Alrowithi, Faisal Qarah, Sakhar Alkhereyf, Arwa Omayrah, Mohammed Al-Saleem, Amal Al-Shammari, Maryam Saif, Raeda Al-Marzooq, Lamyaa Alqhatani, Anas Al-Manie, Ghassan Al-Ward, Shahad Al-Zaidi, Batool Al-Ghoraibi, Alanoud Al-Shammari, Saad Alrazoq.
+
+#### Data Acquisition, Management and Engineering:
+
+Ali Alotaibi, Abdulrahman Alsaudi, Abdulaziz Asheyban, Areej Alokaili, Norah Alangari, Hamad Alnamazi, Fatima Alsalman, Saleh Alrusayyis, Moneerah Alballa, Omar AlGhamdi, Raneem Alqahtani, Amirah Albinhar, Nour Al-Aldahan, Khalid Alharbi, Hanouf Aljlayl, Fatimah Alzubaidi, Lama Aldossary, Rania Alzahrani, Shoug Alkhalaf.
+
+#### Development and Infrastructure:
+
+Saud AlHamoud, Fahad Alothaimeen, Ahmed Alrowatie, Saad Alajlan, Hassan Almitib, Abdinasir Mohamed, Sultan Alotaibi, Mohammed Alanazi, Mohammed Alsharani, Khalid Aljandal, Faisal Abulnaja, Ahmed Alosaimi, Muhannad Abu Hussain, Nasser Almoffarej, Muhammad Al-Hashem, Ahmed Al-Ghamdi, Amer Ashraf, Abeer Al-khars, Nawaf Babgy, Fevicks Kumar, Islam Gamal, Layla Al-Mutairi, Shroq Al-Ghamdi, Amjad Al-Zahrani, Tjad Clark, Ali bjorn, Meshari Alyami, Abdulrahman Bahkali, Reema Alomair.
+
+#### Project Management:
+
+Naif Shalhoub, Esshaq Almotawa, Sara AlRasheed, Mohammed Alshaalan, Mohammed Albreeh, Nezar Kaaki, Muna Alsahli, Abdullah Aldahami, Faisal Al-Tamimi, Tariq Alrouqi, Sahar Alghamdi, Raghad Abuznadah, Naif Almohammed, Oraib Alhemmyraine, Sarah Binlibdah, Shrooq Almohamdi.
+
+#### Human Evaluators:
+
+Amal Almohammadi, Badr almalki, Amjad Alsaeed, Alhanouf Alotaibi, Rajaa Almalki, Maryam Alasmari, Maha Awaji, Fatima Alshehri, Maryam ALshuwaiman, Ebtesam Alzahrani, Yasmeen Al-gahtani, Atheer Almusailem, Rehab Almalky, Shahad Alsulami, Abdullah Albalawi, Abeer Alqahtani, Lama Alrajeh, Shahad Aqeel, Yasir Alharbi, Rassil Al-Otaibi, Khulud Alawadh, Fatimah Almutairi, Suad Alkhamshi, Abdulrahman Alasmari, Goot Alqahtani, alhanouf Alfoaim, Rawan Aljohani, Aisha Almutairi.

sources/marian-ar-en-README.md

@@ -0,0 +1,151 @@
+---
+language:
+- ar
+- en
+tags:
+- translation
+- opus-mt-tc
+license: cc-by-4.0
+model-index:
+- name: opus-mt-tc-big-ar-en
+  results:
+  - task:
+      name: Translation ara-eng
+      type: translation
+      args: ara-eng
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: ara eng devtest
+    metrics:
+    - name: BLEU
+      type: bleu
+      value: 42.6
+  - task:
+      name: Translation ara-eng
+      type: translation
+      args: ara-eng
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: ara-eng
+    metrics:
+    - name: BLEU
+      type: bleu
+      value: 47.3
+  - task:
+      name: Translation ara-eng
+      type: translation
+      args: ara-eng
+    dataset:
+      name: tico19-test
+      type: tico19-test
+      args: ara-eng
+    metrics:
+    - name: BLEU
+      type: bleu
+      value: 44.4
+---
+# opus-mt-tc-big-ar-en
+
+Neural machine translation model for translating from Arabic (ar) to English (en).
+
+This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train).
+
+* Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.)
+
+```
+@inproceedings{tiedemann-thottingal-2020-opus,
+    title = "{OPUS}-{MT} {--} Building open translation services for the World",
+    author = {Tiedemann, J{\"o}rg  and Thottingal, Santhosh},
+    booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation",
+    month = nov,
+    year = "2020",
+    address = "Lisboa, Portugal",
+    publisher = "European Association for Machine Translation",
+    url = "https://aclanthology.org/2020.eamt-1.61",
+    pages = "479--480",
+}
+
+@inproceedings{tiedemann-2020-tatoeba,
+    title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}",
+    author = {Tiedemann, J{\"o}rg},
+    booktitle = "Proceedings of the Fifth Conference on Machine Translation",
+    month = nov,
+    year = "2020",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2020.wmt-1.139",
+    pages = "1174--1182",
+}
+```
+
+## Model info
+
+* Release: 2022-03-09
+* source language(s): afb ara arz
+* target language(s): eng
+* model: transformer-big
+* data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
+* tokenization: SentencePiece (spm32k,spm32k)
+* original model: [opusTCv20210807+bt_transformer-big_2022-03-09.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-eng/opusTCv20210807+bt_transformer-big_2022-03-09.zip)
+* more information released models: [OPUS-MT ara-eng README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-eng/README.md)
+
+## Usage
+
+A short example code:
+
+```python
+from transformers import MarianMTModel, MarianTokenizer
+
+src_text = [
+    "اتبع قلبك فحسب.",
+    "وين راهي دّوش؟"
+]
+
+model_name = "pytorch-models/opus-mt-tc-big-ar-en"
+tokenizer = MarianTokenizer.from_pretrained(model_name)
+model = MarianMTModel.from_pretrained(model_name)
+translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True))
+
+for t in translated:
+    print( tokenizer.decode(t, skip_special_tokens=True) )
+
+# expected output:
+#     Just follow your heart.
+#     Wayne Rahi Dosh?
+```
+
+You can also use OPUS-MT models with the transformers pipelines, for example:
+
+```python
+from transformers import pipeline
+pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-ar-en")
+print(pipe("اتبع قلبك فحسب."))
+
+# expected output: Just follow your heart.
+```
+
+## Benchmarks
+
+* test set translations: [opusTCv20210807+bt_transformer-big_2022-03-09.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-eng/opusTCv20210807+bt_transformer-big_2022-03-09.test.txt)
+* test set scores: [opusTCv20210807+bt_transformer-big_2022-03-09.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-eng/opusTCv20210807+bt_transformer-big_2022-03-09.eval.txt)
+* benchmark results: [benchmark_results.txt](benchmark_results.txt)
+* benchmark output: [benchmark_translations.zip](benchmark_translations.zip)
+
+| langpair | testset | chr-F | BLEU  | #sent | #words |
+|----------|---------|-------|-------|-------|--------|
+| ara-eng | tatoeba-test-v2021-08-07 | 0.63477 | 47.3 | 10305 | 76975 |
+| ara-eng | flores101-devtest | 0.66987 | 42.6 | 1012 | 24721 |
+| ara-eng | tico19-test | 0.68521 | 44.4 | 2100 | 56323 |
+
+## Acknowledgements
+
+The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland.
+
+## Model conversion info
+
+* transformers version: 4.16.2
+* OPUS-MT git hash: 3405783
+* port time: Wed Apr 13 18:17:57 EEST 2022
+* port machine: LM0-400-22516.local

sources/marian-en-ar-README.md

@@ -0,0 +1,155 @@
+---
+language:
+- ar
+- en
+tags:
+- translation
+- opus-mt-tc
+license: cc-by-4.0
+model-index:
+- name: opus-mt-tc-big-en-ar
+  results:
+  - task:
+      name: Translation eng-ara
+      type: translation
+      args: eng-ara
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: eng ara devtest
+    metrics:
+    - name: BLEU
+      type: bleu
+      value: 29.4
+  - task:
+      name: Translation eng-ara
+      type: translation
+      args: eng-ara
+    dataset:
+      name: tatoeba-test-v2020-07-28
+      type: tatoeba_mt
+      args: eng-ara
+    metrics:
+    - name: BLEU
+      type: bleu
+      value: 20.0
+  - task:
+      name: Translation eng-ara
+      type: translation
+      args: eng-ara
+    dataset:
+      name: tico19-test
+      type: tico19-test
+      args: eng-ara
+    metrics:
+    - name: BLEU
+      type: bleu
+      value: 30.0
+---
+# opus-mt-tc-big-en-ar
+
+Neural machine translation model for translating from English (en) to Arabic (ar).
+
+This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train).
+
+* Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.)
+
+```
+@inproceedings{tiedemann-thottingal-2020-opus,
+    title = "{OPUS}-{MT} {--} Building open translation services for the World",
+    author = {Tiedemann, J{\"o}rg  and Thottingal, Santhosh},
+    booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation",
+    month = nov,
+    year = "2020",
+    address = "Lisboa, Portugal",
+    publisher = "European Association for Machine Translation",
+    url = "https://aclanthology.org/2020.eamt-1.61",
+    pages = "479--480",
+}
+
+@inproceedings{tiedemann-2020-tatoeba,
+    title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}",
+    author = {Tiedemann, J{\"o}rg},
+    booktitle = "Proceedings of the Fifth Conference on Machine Translation",
+    month = nov,
+    year = "2020",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2020.wmt-1.139",
+    pages = "1174--1182",
+}
+```
+
+## Model info
+
+* Release: 2022-02-25
+* source language(s): eng
+* target language(s): afb ara
+* valid target language labels: >>afb<< >>ara<<
+* model: transformer-big
+* data: opusTCv20210807+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
+* tokenization: SentencePiece (spm32k,spm32k)
+* original model: [opusTCv20210807+bt_transformer-big_2022-02-25.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-ara/opusTCv20210807+bt_transformer-big_2022-02-25.zip)
+* more information released models: [OPUS-MT eng-ara README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-ara/README.md)
+* more information about the model: [MarianMT](https://huggingface.co/docs/transformers/model_doc/marian)
+
+This is a multilingual translation model with multiple target languages. A sentence initial language token is required in the form of `>>id<<` (id = valid target language ID), e.g. `>>afb<<`
+
+## Usage
+
+A short example code:
+
+```python
+from transformers import MarianMTModel, MarianTokenizer
+
+src_text = [
+    ">>ara<< I can't help you because I'm busy.",
+    ">>ara<< I have to write a letter. Do you have some paper?"
+]
+
+model_name = "pytorch-models/opus-mt-tc-big-en-ar"
+tokenizer = MarianTokenizer.from_pretrained(model_name)
+model = MarianMTModel.from_pretrained(model_name)
+translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True))
+
+for t in translated:
+    print( tokenizer.decode(t, skip_special_tokens=True) )
+
+# expected output:
+#     لا أستطيع مساعدتك لأنني مشغول.
+#     يجب أن أكتب رسالة هل لديك بعض الأوراق؟
+```
+
+You can also use OPUS-MT models with the transformers pipelines, for example:
+
+```python
+from transformers import pipeline
+pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-ar")
+print(pipe(">>ara<< I can't help you because I'm busy."))
+
+# expected output: لا أستطيع مساعدتك لأنني مشغول.
+```
+
+## Benchmarks
+
+* test set translations: [opusTCv20210807+bt_transformer-big_2022-02-25.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-ara/opusTCv20210807+bt_transformer-big_2022-02-25.test.txt)
+* test set scores: [opusTCv20210807+bt_transformer-big_2022-02-25.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-ara/opusTCv20210807+bt_transformer-big_2022-02-25.eval.txt)
+* benchmark results: [benchmark_results.txt](benchmark_results.txt)
+* benchmark output: [benchmark_translations.zip](benchmark_translations.zip)
+
+| langpair | testset | chr-F | BLEU  | #sent | #words |
+|----------|---------|-------|-------|-------|--------|
+| eng-ara | tatoeba-test-v2021-08-07 | 0.48813 | 19.8 | 10305 | 61356 |
+| eng-ara | flores101-devtest | 0.61154 | 29.4 | 1012 | 21357 |
+| eng-ara | tico19-test | 0.60075 | 30.0 | 2100 | 51339 |
+
+## Acknowledgements
+
+The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland.
+
+## Model conversion info
+
+* transformers version: 4.16.2
+* OPUS-MT git hash: 3405783
+* port time: Wed Apr 13 16:37:31 EEST 2022
+* port machine: LM0-400-22516.local