初始化项目，由ModelHub XC社区提供模型

Model: Nerdsking/Nerdsking-python-coder-7B-i Source: Original Platform
2026-09-10 05:10:16 +08:00
commit 1c5d00b07e
5 changed files with 222 additions and 0 deletions
--- a/.gitattributes
+++ b/.gitattributes
@@ -0,0 +1,38 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz 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
+nerdsking-python-coder-7B-i_Q5_k_m.gguf filter=lfs diff=lfs merge=lfs -text
+nerdsking-python-coder-7B-i-Q6_K_i.gguf filter=lfs diff=lfs merge=lfs -text
+nerdsking-python-coder-7B-i-Q8_0_i.gguf filter=lfs diff=lfs merge=lfs -text
--- a/README.md
+++ b/README.md
@@ -0,0 +1,175 @@
+---
+license: apache-2.0
+language:
+- en
+- pt
+- zh
+- es
+- de
+- it
+- fr
+metrics:
+- type:
+    HumanEval zero-shot pass@1: null
+  value:
+    '86.99': null
+pipeline_tag: text-generation
+tags:
+- code
+---
+
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+#### Model Details
+<p class="justified-text">
+<b>Nerdsking-python-coder-7B-i</b> is a 7B parameter partially uncensored model focused in <b> coding</b>. It was massively trained in python, therefore despite the fact it can code in other languages as well, the performance will be not in the same level as the one achieved while using python.
+</p>
+<i>Key Characteristics:</i>
+
+- Parameter count: 7B
+- Primary domain: Python programming
+- Secondary capabilities: General coding, technical English
+- Training focus: Python logic, standard library usage, algorithmic reasoning
+- Alignment: Partially uncensored (developer-oriented)
+<br>
+<p>
+
+#### Nerdsking Python Coder Family
+
+🧠 <a href="https://huggingface.co/Nerdsking/nerdsking-python-coder-3B-i"> Nerdsking Python Coder 3B-i </a><br>
+🧠 <a href="https://huggingface.co/Nerdsking/Nerdsking-python-coder-7B-i"> Nerdsking Python Coder 7B-i </a>
+<br>
+<p>
+  
+#### Benchmark
+<p class="justified-text">
+After intense refining, <b>Nerdsking-python-coder-7B-i</b> has achieved <b>86.99 in HumanEval (bf16)</b>, ranking it amongst the highest-performing Python-focused 7B models ever reported on HumanEval. Surpassing even much bigger models in that area. 
+</p>
+<i>Benchmark details (164 tasks):</i>
+
+- official HumanEval execution protocol - test suites executed via `exec()`
+- zero-shot pass@1
+- dtype == "bfloat16"
+- temperature = 0.1
+- do_sample = False
+- evaluated on fully merged weights
+- Prompting: Chat-formatted with a fixed system prompt (“You are an expert Python coding assistant.”)
+- Quantization: None (unquantized weights - bf16)
+<p class="justified-text">
+<i>The configuration above is fully disclosed to support reproducibility and fair comparison.</i>
+</p>
+<p class="justified-text">
+<i> Note: Quantized variants (INT4/INT6) may exhibit lower HumanEval scores due to reduced numerical precision.</i>
+</p>
+
+
+#### Comparison Table
+
+<table>
+  <thead>
+    <tr>
+      <th>Model name</th>
+      <th>Approx. HumanEval Pass@1 (%)</th>
+      <th>Notes / Source</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td><strong>Nerdsking-python-coder-7B-i</strong></td>
+      <td><strong>86.99</strong></td>
+      <td>Evaluated score (zero-shot, strict HumanEval pass@1, using unquantized weigths bf16)</td>
+    </tr>
+    <tr>
+      <td>Qwen2.5-Coder-7B</td>
+      <td>~74–76</td>
+      <td>Community evaluation (OpenCompass run); figures vary by harness/settings</td>
+    </tr>
+    <tr>
+      <td>DeepSeek-Coder-6.7B</td>
+      <td>~72–73</td>
+      <td>Official DeepSeek report and independent replications; close to strict HumanEval protocol</td>
+    </tr>
+    <tr>
+      <td>CodeLlama-7B</td>
+      <td>~33–35</td>
+      <td>Meta technical report</td>
+    </tr>
+    <tr>
+      <td>Wizard Coder 7B*</td>
+      <td>~57–59</td>
+      <td>Community benchmarks; strong instruction-following but less consistent zero-shot behavior</td>
+    </tr>
+  </tbody>
+</table>
+<p class="justified-text">
+  
+</p>
+
+<hr>
+
+
+#### Benchmark tool used
+
+https://github.com/nerdskingcom/gguf-humaneval-benchmark
+
+Install it using:
+
+<code>
+ pip install gguf-humaneval-benchmark
+</code>
+
+Instructions after install:
+
+<code>
+ gguf-humaneval-benchmark --help
+</code>
+
+<hr>
+
+
+#### S.o.n.n.
+<p class="justified-text">
+The model was treated under <b>"s.o.n.n."</b> (<i>singular omni neural network</i>), a concept created by IPMN at Nerdsking.com that is both a precise way of fine tunning/altering existing models, as well a foundational concept for a broader AI architecture standard currently under active research and development.
+</p>
+<i>When applied to pre-existing models, allows:</i>
+
+- parameter-preserving refinement methodology
+- focused global behavioral shaping, instead of task-local adapters
+- avoidance of fragmentation, very common in multi-adapter or task-siloed approaches
+
+
+
+#### Quick Start (Inference)
+
+<code>
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "Nerdsking/Nerdsking-python-coder-7B-i"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype="bfloat16",
+    device_map="auto"
+)
+
+prompt = "Write a Python function that checks if a number is prime."
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=200)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+</code>
+
+#### Ethical & Safety Notes
+<p class="justified-text">
+This model is intended for technical and research use.
+Due to relaxed alignment constraints, outputs should be reviewed before deployment in production or public-facing systems.
+</p>
+
+#### Citation
+
+If you use this model in research and/or benchmarking, please cite:
+
+Nerdsking-python-coder-7B-i,
+Iran Necho (IPMN) / Nerdsking.com
--- a/nerdsking-python-coder-7B-i-Q6_K_i.gguf
+++ b/nerdsking-python-coder-7B-i-Q6_K_i.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7d782b308ca24dd609084c37e24874dfc9a86c45b9efdf62eac4091fd71a982e
+size 6254198944
--- a/nerdsking-python-coder-7B-i-Q8_0_i.gguf
+++ b/nerdsking-python-coder-7B-i-Q8_0_i.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:14debb1f63ae124f24ef8fa1b251ca7e8cc330d05862b1c8e00142b486ea20ae
+size 8098525344
--- a/nerdsking-python-coder-7B-i_Q5_k_m.gguf
+++ b/nerdsking-python-coder-7B-i_Q5_k_m.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:74aeb43e460052991a1fd37b7adeefaf8932591160cbc3c0a6cddaec3dd224f8
+size 5444831392