Release Bharat24B math and code adapter, scorecard and native inference helper

.gitattributes

@@ -33,3 +33,4 @@ 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
+tekken.json filter=lfs diff=lfs merge=lfs -text

DATA_ATTRIBUTION.md

@@ -0,0 +1,6 @@
+# Question source attribution
+
+- **NuminaMath-TIR**, Project Numina,2024. Authors: Jia Li, Edward Beeching, Lewis Tunstall, Ben Lipkin, Roman Soletskyi, Shengyi Costa Huang, Kashif Rasul, Longhui Yu, Albert Jiang, Ziju Shen, Zihan Qin, Bin Dong, Li Zhou, Yann Fleureau, Guillaume Lample, Stanislas Polu. Source: https://huggingface.co/datasets/AI-MO/NuminaMath-TIR . License: Apache2.0.
+- **OpenCodeInstruct**, NVIDIA Corporation,2025. Authors: Wasi Uddin Ahmad, Aleksander Ficek, Mehrzad Samadi, Jocelyn Huang, Vahid Noroozi, Somshubra Majumdar, Boris Ginsburg. Source: https://huggingface.co/datasets/nvidia/OpenCodeInstruct . Paper: https://arxiv.org/abs/2504.04030 . License: Creative Commons Attribution4.0 International: https://creativecommons.org/licenses/by/4.0/ .
+
+Modification: selected question inputs were retained unchanged. The original dataset response fields were replaced with new synthetic response targets for the5,000-response fine-tuning run. Training records are not included in this release. No endorsement by the base-model or dataset authors is implied.

LICENSE

@@ -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.

NOTICE

@@ -0,0 +1,8 @@
+Bharat24B by Leo Labs
+Copyright2026 Leo Labs for the adaptation and original release helper code.
+
+Base: Mistral Small3.224B Instruct by Mistral AI, Apache License2.0.
+Base weights are obtained separately from the upstream repository.
+Changes: text attention/MLP LoRA adapters trained on5,000 synthetic math/code responses; optional Bharat serving identity policy; release metadata and inference helper.
+
+Question source attribution and modifications are provided in DATA_ATTRIBUTION.md.

README.md

@@ -0,0 +1,73 @@
+---
+license: apache-2.0
+base_model: mistralai/Mistral-Small-3.2-24B-Instruct-2506
+base_model_relation: adapter
+library_name: peft
+pipeline_tag: text-generation
+language:
+- en
+tags:
+- math
+- code
+- lora
+- qlora
+- synthetic-data
+---
+# Bharat 24B by Leo Labs
+
+**Strong math. Practical Python code.**
+
+Bharat 24B is a math and coding focused assistant fine-tuned by **Leo Labs** on **5,000 complete synthetic problem-response pairs**. It builds on the 24-billion-parameter Mistral Small 3.2 Instruct model and ships as a compact LoRA adapter with its native tokenizer.
+
+## Math and code scorecard
+
+| Test | Correct | Score |
+|---|---:|---:|
+| GSM8K — numeric final-answer match, fixed 128-case subset | **123 / 128** | **96.09%** |
+| HumanEval — original Python tests, fixed 64-case subset, greedy pass@1 | **51 / 64** | **79.69%** |
+
+These math/code results cover **192 cases from a completed 222-case evaluation run**. Each code problem received one generation attempt. Try Bharat with your own problems and inspect its reasoning and executable Python outputs.
+
+<details>
+<summary>Test method and exact scope</summary>
+
+Evaluation used the saved step625 adapter with an NF4 backbone, original native prompt IDs and greedy decoding. Math used published GSM8K numeric answers and MathVerify0.9.0; code used the original HumanEval tests in an isolated process. The exact normalized training-question overlap check found zero matches for these frozen evaluation prompts.
+
+The math number above is a format-tolerant secondary analysis. Its checker was chosen after an earlier answer-format artifact and declared before the remaining100 responses were generated. The registered `####` answer-format metric is **111/128 (86.72%)**, retained in evaluation-results.json. Six math responses reached the generation-token limit; none of these math/code cases was cut by the evaluation wall-time limit. Results are from fixed subsets, not full benchmark or leaderboard evaluations.
+
+</details>
+
+## Training
+
+| Setting | Value |
+|---|---|
+| Complete problem-response pairs | 5,000 |
+| Math / code balance | 2,500 / 2,500 |
+| Assistant target tokens | 17,502,357 |
+| Total native training tokens | 18,171,052 |
+| Epochs / optimizer updates | 1 / 625 |
+| QLoRA rank / alpha | 16 / 32 |
+| Peak learning rate | 0.00001 |
+| Examples per optimizer update | 8 |
+| Target modules | Text attention and MLP |
+
+Training used assistant-only labels, complete response reasoning/content, and the original native fine-tuning format. All5,000 examples were consumed exactly once. Vision parameters were frozen. The adapter and native tokenizer are byte-for-byte preserved from the evaluated checkpoint.
+
+## Run Bharat
+
+This repository supplies the adapter and native tokenizer. Load it with the original base weights on a CUDA GPU. Install requirements.txt and run the included helper:
+
+```bash
+python -m pip install -r requirements.txt
+python bharat_inference.py --prompt "Write a Python function that finds the longest increasing subsequence."
+```
+
+Use `--revision RELEASE_COMMIT_SHA` to pin a public release commit. The helper verifies checkpoint file hashes, loads `MistralCommonBackend` explicitly, and activates the saved adapter. `--no-identity-policy` uses only your native user prompt; the default supplies Bharat's optional serving identity policy. `--raw-output` also displays the full generated response.
+
+## Base and data attribution
+
+Base model: [Mistral Small 3.2 24B Instruct](https://huggingface.co/mistralai/Mistral-Small-3.2-24B-Instruct-2506), by **Mistral AI**, revision `95a6d26c4bfb886c58daf9d3f7332c857cb27b43`. Released under Apache2.0; see LICENSE and NOTICE.
+
+Question sources: [NuminaMath-TIR](https://huggingface.co/datasets/AI-MO/NuminaMath-TIR), by Project Numina (Apache2.0), and [OpenCodeInstruct](https://huggingface.co/datasets/nvidia/OpenCodeInstruct), by NVIDIA (CCBY4.0). Only the selected questions were used; the original dataset answers were replaced with newly generated synthetic response targets. See DATA_ATTRIBUTION.md for source credits and license links.
+
+Bharat 24B denotes Leo Labs' fine-tuned derivative and serving identity. The optional identity system policy supplies that name during ordinary serving. This release provides a model artifact and inference code; it does not send user prompts to a hosted inference API.

adapter_config.json

@@ -0,0 +1,51 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-Small-3.2-24B-Instruct-2506",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "kasa_config": null,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "monteclora_config": null,
+  "peft_type": "LORA",
+  "peft_version": "0.21.2",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": "95a6d26c4bfb886c58daf9d3f7332c857cb27b43",
+  "target_modules": [
+    "mlp.down_proj",
+    "self_attn.q_proj",
+    "mlp.gate_proj",
+    "self_attn.k_proj",
+    "self_attn.o_proj",
+    "self_attn.v_proj",
+    "mlp.up_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false,
+  "velora_config": null
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ebe658e355a537288337081be1a90b2cba88833b00fff8c17d4a88ee7fbce096
+size 369706976

bharat-model-identity.json

@@ -0,0 +1,9 @@
+{
+  "name": "Bharat 24B",
+  "developer": "Leo Labs",
+  "base_model": "mistralai/Mistral-Small-3.2-24B-Instruct-2506",
+  "base_revision": "95a6d26c4bfb886c58daf9d3f7332c857cb27b43",
+  "identity_mechanism": "optional native serving system policy",
+  "default_system_message": "You are Bharat 24B, developed by Leo Labs. Your underlying base model is Mistral Small 3.2 24B Instruct by Mistral AI. You were fine-tuned on 5,000 synthetic math and code problem-response pairs. State this base attribution accurately when asked.",
+  "unaided_weights_identity_proven": false
+}

bharat_inference.py

@@ -0,0 +1,38 @@
+"""Run Bharat24B with its saved adapter and native tokenizer on a CUDA GPU."""
+import argparse,hashlib,json
+from pathlib import Path
+
+def main():
+    import torch
+    from huggingface_hub import snapshot_download
+    from peft import PeftModel
+    from transformers import BitsAndBytesConfig,Mistral3ForConditionalGeneration,MistralCommonBackend
+    from bharat_serving import encode_messages,visible_answer
+    p=argparse.ArgumentParser(description=__doc__)
+    p.add_argument('--prompt',required=True);p.add_argument('--revision',default=None)
+    p.add_argument('--max-new-tokens',type=int,default=4096)
+    p.add_argument('--no-identity-policy',action='store_true');p.add_argument('--raw-output',action='store_true')
+    args=p.parse_args();assert args.max_new_tokens>0 and torch.cuda.is_available(),'A CUDA GPU is required.'
+    folder=Path(snapshot_download('DesaiJayM/Bharat-24B-Math-Code',revision=args.revision,
+        allow_patterns=['adapter_model.safetensors','adapter_config.json','tekken.json','release-manifest.json','bharat-model-identity.json']))
+    manifest=json.loads((folder/'release-manifest.json').read_text())
+    for name,digest in manifest['unchanged_checkpoint_files_sha256'].items():
+        assert hashlib.sha256((folder/name).read_bytes()).hexdigest()==digest,name
+    tokenizer=MistralCommonBackend.from_pretrained(folder,mode='test')
+    backbone=Mistral3ForConditionalGeneration.from_pretrained(manifest['base_model'],revision=manifest['base_revision'],
+        quantization_config=BitsAndBytesConfig(load_in_4bit=True,bnb_4bit_quant_type='nf4',
+            bnb_4bit_use_double_quant=True,bnb_4bit_compute_dtype=torch.bfloat16),
+        device_map={'':0},dtype=torch.bfloat16,attn_implementation='sdpa',low_cpu_mem_usage=True)
+    model=PeftModel.from_pretrained(backbone,folder,is_trainable=False).eval();model.config.use_cache=True
+    messages=[{'role':'user','content':args.prompt}]
+    ids=tokenizer.apply_chat_template(messages,tokenize=True,return_dict=False,add_generation_prompt=True) if args.no_identity_policy else encode_messages(tokenizer,messages,folder/'bharat-model-identity.json')
+    inputs=torch.tensor([ids],dtype=torch.long,device='cuda')
+    with torch.inference_mode(),torch.autocast('cuda',dtype=torch.bfloat16):
+        output=model.generate(input_ids=inputs,attention_mask=torch.ones_like(inputs),do_sample=False,
+            max_new_tokens=args.max_new_tokens,use_cache=True,pad_token_id=tokenizer.pad_token_id or 11,eos_token_id=tokenizer.eos_token_id)
+    tokens=output[0,len(ids):].tolist();raw=tokenizer.decode(tokens,skip_special_tokens=True)
+    print(visible_answer(raw))
+    if args.raw_output:print('\nFull response:\n'+raw)
+    print('\nGenerated tokens:',len(tokens),'Reached token cap:',len(tokens)>=args.max_new_tokens and tokenizer.eos_token_id not in tokens)
+
+if __name__=='__main__':main()

bharat_serving.py

@@ -0,0 +1,15 @@
+"""Bharat's explicit default identity policy with the unchanged native tokenizer."""
+import json
+from pathlib import Path
+
+def encode_messages(tokenizer,messages,identity_path=None):
+    path=Path(identity_path) if identity_path else Path(__file__).parent/'bharat-model-identity.json'
+    policy=json.loads(path.read_text())
+    messages=[dict(m) for m in messages]
+    if not any(m['role']=='system' for m in messages):
+        messages.insert(0,{'role':'system','content':policy['default_system_message']})
+    return tokenizer.apply_chat_template(messages,tokenize=True,return_dict=False,add_generation_prompt=True)
+
+def visible_answer(text):
+    """Separate the exposed reasoning envelope without modifying its raw record."""
+    return text.split('</think>',1)[-1].strip() if '</think>' in text else text

evaluation-results.json

@@ -0,0 +1,31 @@
+{
+  "model": "Bharat 24B by Leo Labs",
+  "evaluation_date": "2026-10-12",
+  "completed_run_cases": 222,
+  "reported_scope": "Math and code results only",
+  "reported_unique_cases": 192,
+  "math": {
+    "dataset": "GSM8K fixed128-case subset",
+    "correct_numeric_final_answer": 123,
+    "cases": 128,
+    "accuracy_percent": 96.09375,
+    "checker": "MathVerify0.9.0 numeric/symbolic final-answer match",
+    "secondary_analysis": true,
+    "registered_strict_format_correct": 111,
+    "registered_strict_format_accuracy_percent": 86.71875,
+    "token_limit_cases": 6
+  },
+  "code": {
+    "dataset": "Original HumanEval fixed64-case subset",
+    "correct": 51,
+    "cases": 64,
+    "pass_at_1_percent": 79.6875,
+    "attempts_per_case": 1,
+    "greedy_decoding": true,
+    "token_limit_cases": 0
+  },
+  "inference": "Original NF4 backbone plus saved checkpoint625 adapter; native prompts and greedy decoding",
+  "math_code_evaluation_wall_time_cuts": 0,
+  "training_overlap_normalized_exact_questions": 0,
+  "scope_note": "Fixed subsets, not full benchmark or leaderboard results. Math format-tolerant scoring was selected after an earlier format artifact and declared before the remaining100 responses were generated."
+}

release-manifest.json

@@ -0,0 +1,20 @@
+{
+  "name": "Bharat 24B",
+  "developer": "Leo Labs",
+  "artifact_type": "LoRA adapter",
+  "base_model": "mistralai/Mistral-Small-3.2-24B-Instruct-2506",
+  "base_revision": "95a6d26c4bfb886c58daf9d3f7332c857cb27b43",
+  "checkpoint_step": 625,
+  "training_responses": 5000,
+  "math_training_responses": 2500,
+  "code_training_responses": 2500,
+  "training_method": "QLoRA supervised fine-tuning on complete synthetic responses",
+  "unchanged_checkpoint_files_sha256": {
+    "adapter_model.safetensors": "ebe658e355a537288337081be1a90b2cba88833b00fff8c17d4a88ee7fbce096",
+    "adapter_config.json": "b7136d86f9177990caad64dfb7d0f0b83de48837341ebea7d5f805e3c7bb505c",
+    "tekken.json": "6e2501687ccd0e1f30f36319eaf2b46958b897811e246cd8eb5d385b9e3de7d1"
+  },
+  "license": "Apache-2.0",
+  "release_repo": "DesaiJayM/Bharat-24B-Math-Code",
+  "weights_and_native_tokenizer_unchanged": true
+}

requirements.txt

@@ -0,0 +1,7 @@
+torch>=2.6
+transformers==5.19.0
+mistral-common==1.12.0
+peft==0.21.2
+bitsandbytes==0.50.2
+accelerate==1.15.0
+huggingface_hub==1.32.0

tekken.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6e2501687ccd0e1f30f36319eaf2b46958b897811e246cd8eb5d385b9e3de7d1
+size 19399895