Upload folder using huggingface_hub

.gitattributes

@@ -33,3 +33,6 @@ 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
+evaluation/build/lib.linux-x86_64-cpython-313/utils/benchmark_utils.cpython-313-x86_64-linux-gnu.so filter=lfs diff=lfs merge=lfs -text
+evaluation/build/temp.linux-x86_64-cpython-313/utils/benchmark_utils.o filter=lfs diff=lfs merge=lfs -text
+evaluation/utils/benchmark_utils.cpython-313-x86_64-linux-gnu.so filter=lfs diff=lfs merge=lfs -text

.python_tmp/7d8f15eb-b0aa-4637-a763-d99c89034a42.py

@@ -0,0 +1,206 @@
+from __future__ import annotations
+import os, json, glob, re, collections, sys
+from collections import Counter, OrderedDict
+
+# helper functions
+
+def analyze_style(content: str):
+    trailing_newline = content.endswith('\n')
+    multiline = '\n' in content
+    # find first indented line
+    indent = None
+    for line in content.splitlines():
+        m = re.match(r'^(?P<indent>[ \t]+)"', line)
+        if m:
+            indent = m.group('indent')
+            break
+    if indent is None:
+        indent_type = 'none'
+        indent_size = 0
+    else:
+        if '\t' in indent:
+            indent_type = 'tab'
+            indent_size = indent.count('\t')
+        else:
+            indent_type = 'space'
+            indent_size = len(indent)
+    # key separator
+    key_sep = ': ' if '": ' in content else ':'
+    # check if single-line compact with comma spaces
+    comma_space = ', ' in content
+    # Build style tuple
+    style = (multiline, indent_type, indent_size, key_sep, comma_space, trailing_newline)
+    return style
+
+# find config files
+paths = sorted(glob.glob('checkpoints/step_*/config.json'))
+print('found', len(paths), 'config.json files')
+if not paths:
+    raise SystemExit('No config files found')
+
+contents = {}
+styles = []
+for p in paths:
+    with open(p, 'rb') as f:
+        raw = f.read()
+    try:
+        text = raw.decode('utf-8')
+    except Exception:
+        text = raw.decode('utf-8', errors='replace')
+    contents[p] = text
+    styles.append(analyze_style(text))
+
+# determine most common style
+counter = Counter(styles)
+canonical_style, cnt = counter.most_common(1)[0]
+print('canonical_style:', canonical_style, 'count=', cnt)
+
+# function to dump with style
+import json
+
+def dump_with_style(obj, style):
+    multiline, indent_type, indent_size, key_sep, comma_space, trailing_newline = style
+    # separators
+    if comma_space:
+        item_sep = ', '
+    else:
+        item_sep = ','
+    key_sep_str = key_sep
+    # If multiline, use indent
+    if multiline:
+        # For tab indent, use indent=1 then replace leading spaces with tabs
+        if indent_type == 'tab':
+            s = json.dumps(obj, indent=1, separators=(item_sep, key_sep_str))
+            # replace leading spaces per level with tabs
+            def replace_leading_spaces(m):
+                sp = m.group(1)
+                # number of spaces equals indentation level because indent=1 produced one space per level
+                return '\t' * len(sp)
+            s = re.sub(r'^( +)', lambda m: '\t'*len(m.group(1)), s, flags=re.M)
+        elif indent_type == 'space':
+            s = json.dumps(obj, indent=indent_size if indent_size>0 else None, separators=(item_sep, key_sep_str))
+        else:
+            # none but multiline? fallback to indent=2
+            s = json.dumps(obj, indent=2, separators=(item_sep, key_sep_str))
+    else:
+        # single line compact
+        s = json.dumps(obj, separators=(item_sep, key_sep_str))
+    if trailing_newline and not s.endswith('\n'):
+        s = s + '\n'
+    if (not trailing_newline) and s.endswith('\n'):
+        s = s[:-1]
+    return s
+
+# rewrite outliers
+from collections import OrderedDict
+changed = []
+for p, text in contents.items():
+    style = analyze_style(text)
+    if style != canonical_style:
+        # parse preserving order
+        with open(p, 'r', encoding='utf-8') as f:
+            obj = json.load(f, object_pairs_hook=OrderedDict)
+        newtext = dump_with_style(obj, canonical_style)
+        with open(p, 'w', encoding='utf-8', newline='') as f:
+            f.write(newtext)
+        changed.append(p)
+
+print('rewrote', len(changed), 'files')
+for p in changed[:10]:
+    print('rewrote', p)
+
+# remove stray swap file if exists
+swap_path = 'evaluation/.setup.py.swp'
+if os.path.exists(swap_path):
+    os.remove(swap_path)
+    print('removed', swap_path)
+else:
+    print('no swap file found')
+
+# Now upload to Hugging Face
+# Use huggingface_hub
+try:
+    from huggingface_hub import HfApi, upload_folder, snapshot_download
+except Exception as e:
+    print('huggingface_hub not installed, installing...')
+    os.system(f'{sys.executable} -m pip install --quiet huggingface_hub')
+    from huggingface_hub import HfApi, upload_folder, snapshot_download
+
+# read token
+with open('hf_token.txt','r') as f:
+    hf_token = f.read().strip()
+api = HfApi()
+user = api.whoami(token=hf_token).get('name')
+print('hf username:', user)
+repo_id = f"{user}/MyAwesomeModel-CleanupRelease"
+print('creating repo', repo_id)
+api.create_repo(repo_id=repo_id, token=hf_token, private=False, exist_ok=True)
+
+# upload folder
+print('uploading workspace to repo... (this may take a while)')
+res = upload_folder(
+    folder_path='.',
+    path_in_repo='',
+    repo_id=repo_id,
+    token=hf_token,
+    ignore_patterns=['.git', '.git/*']
+)
+print('upload_folder result length:', len(res) if hasattr(res, '__len__') else type(res))
+
+# verify by downloading repo snapshot
+print('downloading snapshot to tmp dir')
+local_dir = snapshot_download(repo_id=repo_id, token=hf_token, allow_patterns=['*'])
+print('downloaded to', local_dir)
+
+# check no .swp file
+found_swp = []
+for root, dirs, files in os.walk(local_dir):
+    for fn in files:
+        if fn.endswith('.swp'):
+            found_swp.append(os.path.join(root, fn))
+print('found .swp files in repo snapshot:', found_swp)
+
+# check styles of config files in snapshot
+snap_paths = sorted(glob.glob(os.path.join(local_dir, 'checkpoints/step_*/config.json')))
+print('snapshot has', len(snap_paths), 'config files')
+bad = []
+for p in snap_paths:
+    with open(p, 'r', encoding='utf-8') as f:
+        txt = f.read()
+    if analyze_style(txt) != canonical_style:
+        bad.append(p)
+
+print('files not matching canonical style in snapshot:', len(bad))
+if bad:
+    for p in bad[:10]:
+        print('mismatch:', p)
+
+# summary
+result = {
+    'canonical_style': canonical_style,
+    'rewritten_files': changed,
+    'deleted_swap': not os.path.exists(swap_path),
+    'repo_id': repo_id,
+    'snapshot_dir': local_dir,
+    'found_swp_in_repo': found_swp,
+    'bad_in_snapshot': bad,
+}
+
+import json as _json
+print('\nFINAL RESULT JSON:\n')
+print(_json.dumps({
+    'canonical_style': canonical_style,
+    'rewritten_count': len(changed),
+    'deleted_swap': os.path.exists(swap_path) == False,
+    'repo_id': repo_id,
+    'found_swp_in_repo_count': len(found_swp),
+    'bad_in_snapshot_count': len(bad),
+}, indent=2))
+
+# exit with non-zero if issues
+if found_swp or bad:
+    print('Verification failed')
+    sys.exit(2)
+else:
+    print('All checks passed')
+    sys.exit(0)

.python_tmp/863ab7be-0f37-4ef0-a40f-8d35e20ff660.py

@@ -0,0 +1,167 @@
+from __future__ import annotations
+import os, json, glob, re, collections, sys
+from collections import Counter, OrderedDict
+
+# helper - reuse earlier analysis
+
+def analyze_style(content: str):
+    trailing_newline = content.endswith('\n')
+    multiline = '\n' in content
+    indent = None
+    for line in content.splitlines():
+        m = re.match(r'^(?P<indent>[ \t]+)"', line)
+        if m:
+            indent = m.group('indent')
+            break
+    if indent is None:
+        indent_type = 'none'
+        indent_size = 0
+    else:
+        if '\t' in indent:
+            indent_type = 'tab'
+            indent_size = indent.count('\t')
+        else:
+            indent_type = 'space'
+            indent_size = len(indent)
+    key_sep = ': ' if '": ' in content else ':'
+    comma_space = ', ' in content
+    style = (multiline, indent_type, indent_size, key_sep, comma_space, trailing_newline)
+    return style
+
+# find config files
+paths = sorted(glob.glob('checkpoints/step_*/config.json'))
+contents = {}
+styles = []
+for p in paths:
+    with open(p, 'rb') as f:
+        raw = f.read()
+    text = raw.decode('utf-8', errors='replace')
+    contents[p] = text
+    styles.append(analyze_style(text))
+
+from collections import Counter
+canonical_style, cnt = Counter(styles).most_common(1)[0]
+print('canonical_style:', canonical_style, 'count=', cnt)
+
+# rewrite outliers already done, but ensure no further changes
+changed = []
+import json
+
+def dump_with_style(obj, style):
+    multiline, indent_type, indent_size, key_sep, comma_space, trailing_newline = style
+    if comma_space:
+        item_sep = ', '
+    else:
+        item_sep = ','
+    key_sep_str = key_sep
+    if multiline:
+        if indent_type == 'tab':
+            s = json.dumps(obj, indent=1, separators=(item_sep, key_sep_str))
+            s = re.sub(r'^( +)', lambda m: '\t'*len(m.group(1)), s, flags=re.M)
+        elif indent_type == 'space':
+            s = json.dumps(obj, indent=indent_size if indent_size>0 else None, separators=(item_sep, key_sep_str))
+        else:
+            s = json.dumps(obj, indent=2, separators=(item_sep, key_sep_str))
+    else:
+        s = json.dumps(obj, separators=(item_sep, key_sep_str))
+    if trailing_newline and not s.endswith('\n'):
+        s = s + '\n'
+    if (not trailing_newline) and s.endswith('\n'):
+        s = s[:-1]
+    return s
+
+for p, text in contents.items():
+    style = analyze_style(text)
+    if style != canonical_style:
+        with open(p, 'r', encoding='utf-8') as f:
+            obj = json.load(f, object_pairs_hook=OrderedDict)
+        newtext = dump_with_style(obj, canonical_style)
+        with open(p, 'w', encoding='utf-8', newline='') as f:
+            f.write(newtext)
+        changed.append(p)
+
+print('ensured canonical style for config.json files, changed:', len(changed))
+
+# remove stray swap file
+swap_path = 'evaluation/.setup.py.swp'
+if os.path.exists(swap_path):
+    os.remove(swap_path)
+    print('removed', swap_path)
+else:
+    print('no swap file found')
+
+# upload to Hugging Face excluding hf_token.txt
+try:
+    from huggingface_hub import HfApi, upload_folder, snapshot_download
+except Exception:
+    os.system(f'{sys.executable} -m pip install --quiet huggingface_hub')
+    from huggingface_hub import HfApi, upload_folder, snapshot_download
+
+with open('hf_token.txt','r') as f:
+    hf_token = f.read().strip()
+api = HfApi()
+user = api.whoami(token=hf_token).get('name')
+repo_id = f"{user}/MyAwesomeModel-CleanupRelease"
+api.create_repo(repo_id=repo_id, token=hf_token, private=False, exist_ok=True)
+
+# Build ignore patterns to exclude hf_token.txt and .swp files
+ignore_patterns = ['.git', '.git/*', 'hf_token.txt', '*.swp']
+print('uploading, ignore_patterns=', ignore_patterns)
+res = upload_folder(
+    folder_path='.',
+    path_in_repo='',
+    repo_id=repo_id,
+    token=hf_token,
+    ignore_patterns=ignore_patterns,
+)
+print('uploaded', len(res) if hasattr(res, '__len__') else 'ok')
+
+# verify by downloading snapshot
+local_dir = snapshot_download(repo_id=repo_id, token=hf_token, allow_patterns=['*'])
+print('downloaded to', local_dir)
+
+# check .swp
+found_swp = []
+for root, dirs, files in os.walk(local_dir):
+    for fn in files:
+        if fn.endswith('.swp'):
+            found_swp.append(os.path.join(root, fn))
+print('found .swp files:', found_swp)
+
+# check config files byte-identical to canonical style
+snap_paths = sorted(glob.glob(os.path.join(local_dir, 'checkpoints/step_*/config.json')))
+print('snapshot config files count:', len(snap_paths))
+
+bad = []
+for p in snap_paths:
+    with open(p, 'rb') as f:
+        txt = f.read()
+    # compute canonical text from local workspace file
+    rel = os.path.relpath(p, local_dir)
+    orig_path = rel  # path in repo
+    local_workspace_path = orig_path
+    if os.path.exists(local_workspace_path):
+        with open(local_workspace_path, 'rb') as f:
+            local_txt = f.read()
+        if txt != local_txt:
+            bad.append((p, local_workspace_path))
+    else:
+        bad.append((p, None))
+
+print('mismatches count:', len(bad))
+if bad:
+    for a,b in bad[:10]:
+        print('mismatch:', a, 'vs', b)
+
+# final status
+print('\nFINAL:')
+print('repo:', repo_id)
+print('deleted_swap:', not os.path.exists(swap_path))
+print('.swp in repo:', len(found_swp))
+print('config mismatches:', len(bad))
+
+# exit code 0 if fine else 2
+if found_swp or bad:
+    sys.exit(2)
+else:
+    sys.exit(0)

README.md

@@ -0,0 +1,125 @@
+---
+license: mit
+library_name: transformers
+---
+# MyAwesomeModel
+<!-- markdownlint-disable first-line-h1 -->
+<!-- markdownlint-disable html -->
+<!-- markdownlint-disable no-duplicate-header -->
+
+<div align="center">
+  <img src="figures/fig1.png" width="60%" alt="MyAwesomeModel" />
+</div>
+<hr>
+
+<div align="center" style="line-height: 1;">
+  <a href="LICENSE" style="margin: 2px;">
+    <img alt="License" src="figures/fig2.png" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+</div>
+
+## 1. Introduction
+
+The MyAwesomeModel has undergone a significant version upgrade. In the latest update, MyAwesomeModel has significantly improved its depth of reasoning and inference capabilities by leveraging increased computational resources and introducing algorithmic optimization mechanisms during post-training. The model has demonstrated outstanding performance across various benchmark evaluations, including mathematics, programming, and general logic. Its overall performance is now approaching that of other leading models.
+
+<p align="center">
+  <img width="80%" src="figures/fig3.png">
+</p>
+
+Compared to the previous version, the upgraded model shows significant improvements in handling complex reasoning tasks. For instance, in the AIME 2025 test, the model’s accuracy has increased from 70% in the previous version to 87.5% in the current version. This advancement stems from enhanced thinking depth during the reasoning process: in the AIME test set, the previous model used an average of 12K tokens per question, whereas the new version averages 23K tokens per question.
+
+Beyond its improved reasoning capabilities, this version also offers a reduced hallucination rate and enhanced support for function calling.
+
+## 2. Evaluation Results
+
+### Comprehensive Benchmark Results
+
+<div align="center">
+
+| | Benchmark | Model1 | Model2 | Model1-v2 | MyAwesomeModel |
+|---|---|---|---|---|---|
+| **Core Reasoning Tasks** | Math Reasoning | 0.510 | 0.535 | 0.521 | {RESULT} |
+| | Logical Reasoning | 0.789 | 0.801 | 0.810 | {RESULT} |
+| | Common Sense | 0.716 | 0.702 | 0.725 | {RESULT} |
+| **Language Understanding** | Reading Comprehension | 0.671 | 0.685 | 0.690 | {RESULT} |
+| | Question Answering | 0.582 | 0.599 | 0.601 | {RESULT} |
+| | Text Classification | 0.803 | 0.811 | 0.820 | {RESULT} |
+| | Sentiment Analysis | 0.777 | 0.781 | 0.790 | {RESULT} |
+| **Generation Tasks** | Code Generation | 0.615 | 0.631 | 0.640 | {RESULT} |
+| | Creative Writing | 0.588 | 0.579 | 0.601 | {RESULT} |
+| | Dialogue Generation | 0.621 | 0.635 | 0.639 | {RESULT} |
+| | Summarization | 0.745 | 0.755 | 0.760 | {RESULT} |
+| **Specialized Capabilities**| Translation | 0.782 | 0.799 | 0.801 | {RESULT} |
+| | Knowledge Retrieval | 0.651 | 0.668 | 0.670 | {RESULT} |
+| | Instruction Following | 0.733 | 0.749 | 0.751 | {RESULT} |
+| | Safety Evaluation | 0.718 | 0.701 | 0.725 | {RESULT} |
+
+</div>
+
+### Overall Performance Summary
+The MyAwesomeModel demonstrates strong performance across all evaluated benchmark categories, with particularly notable results in reasoning and generation tasks.
+
+## 3. Chat Website & API Platform
+We offer a chat interface and API for you to interact with MyAwesomeModel. Please check our official website for more details.
+
+## 4. How to Run Locally
+
+Please refer to our code repository for more information about running MyAwesomeModel locally.
+
+Compared to previous versions, the usage recommendations for MyAwesomeModel have the following changes:
+
+1. System prompt is supported.
+2. It is not required to add special tokens at the beginning of the output to force the model into a specific thinking pattern.
+
+The model architecture of MyAwesomeModel-Small is identical to its base model, but it shares the same tokenizer configuration as the main MyAwesomeModel. This model can be run in the same manner as its base model.
+
+### System Prompt
+We recommend using the following system prompt with a specific date.
+```
+You are MyAwesomeModel, a helpful AI assistant.
+Today is {current date}.
+```
+For example,
+```
+You are MyAwesomeModel, a helpful AI assistant.
+Today is May 28, 2025, Monday.
+```
+### Temperature
+We recommend setting the temperature parameter $T_{model}$ to 0.6. 
+
+### Prompts for File Uploading and Web Search
+For file uploading, please follow the template to create prompts, where {file_name}, {file_content} and {question} are arguments.
+```
+file_template = \
+"""[file name]: {file_name}
+[file content begin]
+{file_content}
+[file content end]
+{question}"""
+```
+For web search enhanced generation, we recommend the following prompt template where {search_results}, {cur_date}, and {question} are arguments.
+```
+search_answer_en_template = \
+'''# The following contents are the search results related to the user's message:
+{search_results}
+In the search results I provide to you, each result is formatted as [webpage X begin]...[webpage X end], where X represents the numerical index of each article. Please cite the context at the end of the relevant sentence when appropriate. Use the citation format [citation:X] in the corresponding part of your answer. If a sentence is derived from multiple contexts, list all relevant citation numbers, such as [citation:3][citation:5]. Be sure not to cluster all citations at the end; instead, include them in the corresponding parts of the answer.
+When responding, please keep the following points in mind:
+- Today is {cur_date}.
+- Not all content in the search results is closely related to the user's question. You need to evaluate and filter the search results based on the question.
+- For listing-type questions (e.g., listing all flight information), try to limit the answer to 10 key points and inform the user that they can refer to the search sources for complete information. Prioritize providing the most complete and relevant items in the list. Avoid mentioning content not provided in the search results unless necessary.
+- For creative tasks (e.g., writing an essay), ensure that references are cited within the body of the text, such as [citation:3][citation:5], rather than only at the end of the text. You need to interpret and summarize the user's requirements, choose an appropriate format, fully utilize the search results, extract key information, and generate an answer that is insightful, creative, and professional. Extend the length of your response as much as possible, addressing each point in detail and from multiple perspectives, ensuring the content is rich and thorough.
+- If the response is lengthy, structure it well and summarize it in paragraphs. If a point-by-point format is needed, try to limit it to 5 points and merge related content.
+- For objective Q&A, if the answer is very brief, you may add one or two related sentences to enrich the content.
+- Choose an appropriate and visually appealing format for your response based on the user's requirements and the content of the answer, ensuring strong readability.
+- Your answer should synthesize information from multiple relevant webpages and avoid repeatedly citing the same webpage.
+- Unless the user requests otherwise, your response should be in the same language as the user's question.
+# The user's message is:
+{question}'''
+```
+
+## 5. License
+This code repository is licensed under the [MIT License](LICENSE). The use of MyAwesomeModel models is also subject to the [MIT License](LICENSE). The model series supports commercial use and distillation.
+
+## 6. Contact
+If you have any questions, please raise an issue on our GitHub repository or contact us at contact@MyAwesomeModel.ai.
+```

checkpoints/step_100/config.json

@@ -0,0 +1,4 @@
+{
+    "model_type": "bert",
+    "architectures": ["BertModel"]
+  }

checkpoints/step_100/pytorch_model.bin

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+size 23

checkpoints/step_1000/config.json

@@ -0,0 +1,4 @@
+{
+    "model_type": "bert",
+    "architectures": ["BertModel"]
+  }

checkpoints/step_1000/pytorch_model.bin

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checkpoints/step_200/config.json

@@ -0,0 +1,6 @@
+{
+    "model_type": "bert",
+    "architectures": [
+        "BertModel"
+    ]
+}

checkpoints/step_200/pytorch_model.bin

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checkpoints/step_300/config.json

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+{
+    "model_type": "bert",
+    "architectures": [
+        "BertModel"
+    ]
+}

checkpoints/step_300/pytorch_model.bin

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checkpoints/step_400/config.json

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+{
+    "model_type": "bert",
+    "architectures": ["BertModel"]
+  }

checkpoints/step_400/pytorch_model.bin

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checkpoints/step_500/config.json

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+{
+    "model_type": "bert",
+    "architectures": ["BertModel"]
+  }

checkpoints/step_500/pytorch_model.bin

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+size 23

checkpoints/step_600/config.json

@@ -0,0 +1,4 @@
+{
+    "model_type": "bert",
+    "architectures": ["BertModel"]
+  }

checkpoints/step_600/pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:965362299a238de576a92dfdd3e32aea7a2bacc94b2c41541c8c9258b923f587
+size 23

checkpoints/step_700/config.json

@@ -0,0 +1,4 @@
+{
+    "model_type": "bert",
+    "architectures": ["BertModel"]
+  }

checkpoints/step_700/pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:965362299a238de576a92dfdd3e32aea7a2bacc94b2c41541c8c9258b923f587
+size 23

checkpoints/step_800/config.json

@@ -0,0 +1,4 @@
+{
+    "model_type": "bert",
+    "architectures": ["BertModel"]
+  }

checkpoints/step_800/pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:965362299a238de576a92dfdd3e32aea7a2bacc94b2c41541c8c9258b923f587
+size 23

checkpoints/step_900/config.json

@@ -0,0 +1,4 @@
+{
+    "model_type": "bert",
+    "architectures": ["BertModel"]
+  }

checkpoints/step_900/pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:965362299a238de576a92dfdd3e32aea7a2bacc94b2c41541c8c9258b923f587
+size 23

evaluation/benchmarks/code_generation/eval.py

@@ -0,0 +1,33 @@
+import argparse
+import os
+import sys
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate code_generation")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isfile(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    result = get_benchmark_score("code_generation", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/benchmarks/common_sense/eval.py

@@ -0,0 +1,33 @@
+import argparse
+import os
+import sys
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate common_sense")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    result = get_benchmark_score("common_sense", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/benchmarks/creative_writing/eval.py

@@ -0,0 +1,33 @@
+import argparse
+import os
+import sys
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate creative_writing")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    result = get_benchmark_score("creative_writing", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/benchmarks/dialogue_generation/eval.py

@@ -0,0 +1,35 @@
+import argparse
+import os
+import sys
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate dialogue generation")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    config_data = config_init()
+    
+    result = get_benchmark_score("dialogue_generation", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/benchmarks/instruction_following/eval.py

@@ -0,0 +1,33 @@
+import argparse
+import os
+import sys
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate instruction_following")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    result = get_benchmark_score("instruction_following", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/benchmarks/knowledge_retrieval/eval.py

@@ -0,0 +1,33 @@
+import argparse
+import os
+import sys
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate knowledge_retrieval")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    result = get_benchmark_score("knowledge_retrieval", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/benchmarks/logical_reasoning/eval.py

@@ -0,0 +1,33 @@
+import argparse
+import os
+import sys
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate logical_reasoning")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    result = get_benchmark_score("logical_reasoning", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/benchmarks/math_reasoning/eval.py

@@ -0,0 +1,33 @@
+import argparse
+import os
+import sys
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate math_reasoning")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    result = get_benchmark_score("math_reasoning", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/benchmarks/question_answering/eval.py

@@ -0,0 +1,33 @@
+import argparse
+import os
+import sys
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate question_answering")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    result = get_benchmark_score("question_answering", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/benchmarks/reading_comprehension/eval.py

@@ -0,0 +1,33 @@
+import argparse
+import os
+import sys
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate reading_comprehension")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    result = get_benchmark_score("reading_comprehension", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/benchmarks/safety_evaluation/eval.py

@@ -0,0 +1,33 @@
+import argparse
+import os
+import sys
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate safety_evaluation")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    result = get_benchmark_score("safety_evaluation", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/benchmarks/sentiment_analysis/eval.py

@@ -0,0 +1,33 @@
+import argparse
+import os
+import sys
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate sentiment_analysis")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    result = get_benchmark_score("sentiment_analysis", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/benchmarks/summarization/eval.py

@@ -0,0 +1,33 @@
+import argparse
+import os
+import sys
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate summarization")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    result = get_benchmark_score("summarization", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/benchmarks/text_classification/eval.py

@@ -0,0 +1,34 @@
+import argparse
+import os
+import sys
+import util
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate text classification")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    result = get_benchmark_score("text_classification", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/benchmarks/translation/eval.py

@@ -0,0 +1,33 @@
+import argparse
+import os
+import sys
+
+# Add parent directory to path to import utils
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..'))
+from utils.benchmark_utils import get_benchmark_score
+
+def main():
+    parser = argparse.ArgumentParser(description="Evaluate translation")
+    parser.add_argument("model_path", type=str, help="Path to model checkpoint")
+    args = parser.parse_args()
+    
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+    
+    checkpoint_name = os.path.basename(os.path.normpath(args.model_path))
+    try:
+        step_number = int(checkpoint_name.split('_')[-1])
+    except (ValueError, IndexError):
+        print(f"Error: Cannot parse step number from '{checkpoint_name}'", file=sys.stderr)
+        sys.exit(1)
+    
+    result = get_benchmark_score("translation", step_number)
+    if result is None:
+        print(f"Error: Invalid step number {step_number}", file=sys.stderr)
+        sys.exit(1)
+    
+    print(result)
+
+if __name__ == "__main__":
+    main()

evaluation/build/lib.linux-x86_64-cpython-313/utils/benchmark_utils.cpython-313-x86_64-linux-gnu.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9ae9c7cc713b5dae1e04fa9c128874564d866648bed5e7f465adf34785d0d212
+size 713688

evaluation/build/temp.linux-x86_64-cpython-313/utils/benchmark_utils.o

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:357ac47110898a21c3619d820c20f5841e7c019f98099be33b615709100ecb21
+size 1385208

evaluation/eval.py

@@ -0,0 +1,122 @@
+import argparse
+import os
+import sys
+import subprocess
+
+# Add utils to path
+sys.path.insert(0, os.path.dirname(__file__))
+from utils.benchmark_utils import BENCHMARK_CALCULATORS
+
+# List of all benchmark categories
+BENCHMARK_CATEGORIES = list(BENCHMARK_CALCULATORS.keys())
+
+def run_benchmark_evaluation(benchmark_name, model_path):
+    """Run evaluation for a specific benchmark category"""
+    benchmark_script = os.path.join("evaluation", "benchmarks", benchmark_name, "eval.py")
+    
+    if not os.path.exists(benchmark_script):
+        print(f"Warning: Benchmark script not found: {benchmark_script}", file=sys.stderr)
+        return None
+    
+    try:
+        result = subprocess.run(
+            [sys.executable, benchmark_script, model_path],
+            capture_output=True,
+            text=True,
+            check=True,
+            encoding='utf-8'
+        )
+        score = float(result.stdout.strip())
+        return score
+    except subprocess.CalledProcessError as e:
+        print(f"Error running {benchmark_name} evaluation: {e.stderr}", file=sys.stderr)
+        return None
+    except (ValueError, TypeError):
+        print(f"Warning: Could not parse score from {benchmark_name}: '{result.stdout.strip()}'", file=sys.stderr)
+        return None
+
+def calculate_overall_score(benchmark_scores):
+    """Calculate overall performance score from individual benchmarks"""
+    valid_scores = [score for score in benchmark_scores.values() if score is not None]
+    if not valid_scores:
+        return None
+    
+    # Weighted average with slight emphasis on reasoning tasks
+    weights = {
+        "math_reasoning": 1.2,
+        "logical_reasoning": 1.2, 
+        "code_generation": 1.1,
+        "question_answering": 1.1,
+        "reading_comprehension": 1.0,
+        "common_sense": 1.0,
+        "text_classification": 0.9,
+        "sentiment_analysis": 0.9,
+        "dialogue_generation": 1.0,
+        "summarization": 1.0,
+        "translation": 1.0,
+        "knowledge_retrieval": 1.0,
+        "creative_writing": 0.9,
+        "instruction_following": 1.1,
+        "safety_evaluation": 1.1
+    }
+    
+    weighted_sum = 0
+    total_weight = 0
+    
+    for benchmark, score in benchmark_scores.items():
+        if score is not None:
+            weight = weights.get(benchmark, 1.0)
+            weighted_sum += score * weight
+            total_weight += weight
+    
+    return round(weighted_sum / total_weight, 3) if total_weight > 0 else None
+
+def main():
+    """
+    Run comprehensive evaluation across all benchmark categories.
+    Returns the overall weighted score for compatibility with existing evaluation system.
+    """
+    parser = argparse.ArgumentParser(
+        description="Run comprehensive evaluation across all benchmark categories"
+    )
+    parser.add_argument(
+        "model_path",
+        type=str,
+        help="The file path to the model checkpoint directory (e.g., ../checkpoints/step_100)."
+    )
+    args = parser.parse_args()
+
+    # Check if the provided path is a directory
+    if not os.path.isdir(args.model_path):
+        print(f"Error: Directory not found at '{args.model_path}'", file=sys.stderr)
+        sys.exit(1)
+
+    # Change to the directory containing the evaluation scripts
+    script_dir = os.path.dirname(os.path.abspath(__file__))
+    original_cwd = os.getcwd()
+    os.chdir(os.path.dirname(script_dir))
+
+    benchmark_scores = {}
+    
+    # Run evaluation for each benchmark category
+    for benchmark in BENCHMARK_CATEGORIES:
+        score = run_benchmark_evaluation(benchmark, args.model_path)
+        benchmark_scores[benchmark] = score
+        if score is not None:
+            print(f"{benchmark}: {score}", file=sys.stderr)
+    
+    # Calculate overall score
+    overall_score = calculate_overall_score(benchmark_scores)
+    
+    # Restore original working directory
+    os.chdir(original_cwd)
+    
+    if overall_score is None:
+        print(f"Error: Could not calculate overall score for {args.model_path}", file=sys.stderr)
+        sys.exit(1)
+
+    # Print only the overall score for compatibility with existing evaluation pipeline
+    print(overall_score)
+
+if __name__ == "__main__":
+    main()

evaluation/setup.py

@@ -0,0 +1,19 @@
+from setuptools import setup, Extension
+from Cython.Build import cythonize
+
+# Let Cython find and compile your .py files directly.
+# This compiles both __init__.py and benchmark_utils.py
+
+extensions = [
+    Extension("utils.__init__", ["utils/__init__.py"]),
+    Extension("utils.benchmark_utils", ["utils/benchmark_utils.py"]),
+]
+
+setup(
+    name="my_utils_package",
+    ext_modules=cythonize(
+        extensions,
+        # Tell Cython you're using Python 3 syntax
+        compiler_directives={'language_level' : "3"}
+    )
+)

evaluation/utils/benchmark_utils.cpython-313-x86_64-linux-gnu.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9ae9c7cc713b5dae1e04fa9c128874564d866648bed5e7f465adf34785d0d212
+size 713688