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Model: qingy2024/GRMR-V3-Q4B Source: Original Platform
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README.md
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README.md
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---
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base_model: unsloth/Qwen3-4B-Base
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- qwen
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- trl
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- sft
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license: apache-2.0
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language:
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- en
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---
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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</head>
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<div class="container"><h1>GRMR-V3-Q4B</h1><p>GRMR-V3-Q4B is a fine-tuned version of <a href="https://huggingface.co/unsloth/Qwen3-4B-Base">unsloth/Qwen3-4B-Base</a> specifically optimized for grammar correction tasks.</p><div class="important-note"><p><strong>IMPORTANT:</strong> Please ensure you are using the following sampler settings for optimal results:</p><pre><code>temperature = 0.7
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frequency_penalty = 0.0
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presence_penalty = 0.0
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min_p = 0.01
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top_p = 0.95
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top_k = 40</code></pre></div><h2>Model description</h2><p>GRMR-V3-Q4B is a grammar correction model built on Qwen3 4B base model. It has been fine-tuned on a large dataset of grammar correction examples to help improve text quality by fixing grammatical errors, punctuation, spelling, and other language issues.</p><p>The model uses a specialized chat template that structures inputs as "text" and outputs as "corrected" to maintain a clear distinction between original and corrected content.</p><h3>Model Details</h3><div class="model-meta"><p><strong>Developed by:</strong> qingy2024</p><p><strong>Finetuned from model:</strong> <a href="https://huggingface.co/unsloth/Qwen3-4B-Base">unsloth/Qwen3-4B-Base</a></p><p><strong>Model type:</strong> Qwen3</p><p><strong>Language(s):</strong> English</p><p><strong>License:</strong> apache-2.0</p><p><strong>Training Dataset:</strong> <a href="https://huggingface.co/datasets/qingy2024/grmr-v4-60k">qingy2024/grmr-v4-60k</a></p></div><hr><h2>Manual Testing Examples</h2><p>Here are a few examples of grammar corrections this model can handle:</p><table><thead><tr><th>Original Text</th><th>Corrected Text</th></tr></thead><tbody><tr><td>i dont know weather to bring a umbrella today</td><td>I don't know whether to bring an umbrella today.</td></tr><tr><td>she go to the store yesterday</td><td>She went to the store yesterday.</td></tr><tr><td>they is going to be late for the meeting</td><td>They are going to be late for the meeting.</td></tr><tr><td>the cat laying on the floor all day</td><td>The cat is laying on the floor all day.</td></tr></tbody></table><hr><h2>Training procedure</h2><p>The model was fine-tuned using full parameter fine-tuning (not LoRA) on the GRMR-V4-60K dataset. The training was optimized using the Unsloth framework for efficient training of LLMs.</p><h3>Training hyperparameters</h3><ul><li><strong>Batch size:</strong> 8</li><li><strong>Gradient accumulation steps:</strong> 2</li><li><strong>Learning rate:</strong> 5e-5</li><li><strong>Epochs:</strong> 1</li><li><strong>Optimizer:</strong> AdamW (8-bit)</li><li><strong>Weight decay:</strong> 0.01</li><li><strong>LR scheduler:</strong> Cosine</li><li><strong>Warmup steps:</strong> 180</li><li><strong>Max sequence length:</strong> 16,384</li><li><strong>Training precision:</strong> Mixed precision (BF16 where available, FP16 otherwise)</li></ul><h2>Intended uses & limitations</h2><p>This model is designed for grammar correction tasks. It can be used to:</p><ul><li>Fix grammatical errors in written text</li><li>Correct punctuation</li><li>Address spelling mistakes</li><li>Improve sentence structure and clarity</li></ul><h3>Limitations</h3><ul><li>The model may struggle with highly technical or domain-specific content</li><li>It may not fully understand context-dependent grammar rules in all cases</li><li>Performance may vary for non-standard English or text with multiple errors</li></ul><h2>How to use</h2><p>Projects based on Hugging Face transformers should be able to run this model easily.</p><pre><code class="language-python">from transformers import AutoModelForCausalLM, AutoTokenizer
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# Load model and tokenizer
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model_name = "qingy2024/GRMR-V3-Q4B"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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# Text with grammar errors to correct
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text_to_correct = "i am going to the store tommorow and buy some thing for dinner"
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# Format as messages
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messages = [
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{"role": "user", "content": text_to_correct}
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]
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# Apply the custom chat template
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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# Tokenize and generate
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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outputs = model.generate(
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inputs["input_ids"],
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max_new_tokens=512,
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temperature=0.1,
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do_sample=True
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)
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# Decode and print the corrected text
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corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
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print(corrected_text)</code></pre><h3>Using with the Hugging Face pipeline</h3><pre><code class="language-python">from transformers import pipeline
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pipe = pipeline(
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"text-generation",
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model="qingy2024/GRMR-V3-Q4B",
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torch_dtype="auto",
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device_map="auto"
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)
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messages = [
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{"role": "user", "content": "i dont know weather to bring a umbrella today"}
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]
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result = pipe(
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messages,
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max_new_tokens=100,
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temperature=0.1,
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do_sample=True,
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return_full_text=False
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)[0]["generated_text"]
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print(result)</code></pre><h2>Custom Chat Template</h2><p class="chat-template-info">The model uses a custom chat template with special formatting for grammar correction:</p><ul><li>User inputs are formatted with <code><|text_start|></code> and <code><|text_end|></code> tags</li><li>Model outputs are formatted with <code><|corrected_start|></code> and <code><|corrected_end|></code> tags</li></ul><p>The complete chat template is:</p><pre><code class="language-jinja">{%- for message in messages %}
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{%- if message.role == "user" %}
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{{- '<|text_start|>\n' + message.content + '<|text_end|>\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|corrected_start|>\n' + message.content + '<|corrected_end|>\n' }}
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{%- else %}
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{{- raise('Unknown role: ' + message.role) }}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|corrected_start|>\n' }}
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{%- endif %}</code></pre><h2>Training Dataset</h2><p>The model was fine-tuned on the <a href="https://huggingface.co/datasets/qingy2024/grmr-v4-60k">qingy2024/grmr-v4-60k</a> dataset, which contains 60,000 examples of original text and their grammatically corrected versions.</p><h2>Bias, Risks, and Limitations</h2><ul><li>The model may reflect biases present in the training data</li><li>It may not perform equally well across different writing styles or domains</li><li>The model might occasionally introduce errors or change the meaning of text</li><li>It focuses on grammatical correctness rather than stylistic improvements</li></ul><h2>Citations</h2><pre><code>@misc{qwen3technicalreport,
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title={Qwen3 Technical Report},
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author={Qwen Team},
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year={2025},
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eprint={2505.09388},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2505.09388},
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}</code></pre><h2>Contact</h2><p>For questions or issues related to the model, please reach out via Hugging Face or by creating an issue in the repository.</p></div>
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<style>
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line-height: 1.6;
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padding: 0;
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background-color: #f8f9fa;
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color: #333;
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margin-top: 1.5em;
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margin-bottom: 0.7em;
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color: #007bff;
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text-decoration: underline;
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background-color: #e7f3ff; /* Light blue background */
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border-left: 5px solid #007bff; /* Blue accent border */
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border-radius: 3px;
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width: 100%;
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border: 1px solid #dee2e6;
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background-color: #e9ecef; /* Light gray for headers */
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td:first-child {
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/* font-style: italic; */
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color: #444;
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}
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pre {
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background-color: #f1f3f5;
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padding: 15px;
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ul {
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}
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li {
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margin-bottom: 0.5em;
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}
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hr {
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border: none;
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border-top: 1px solid #e0e0e0;
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margin: 30px 0;
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}
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.model-meta {
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background-color: #f8f9fa;
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padding: 15px;
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border-radius: 5px;
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margin-bottom: 20px;
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border: 1px solid #e9ecef;
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.model-meta p { margin-bottom: 0.5em; }
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.model-meta strong { color: #333; }
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/* Specific styling for chat template explanation */
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.chat-template-info span {
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font-weight: bold;
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color: #0056b3;
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}
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</style></html>
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added_tokens.json
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added_tokens.json
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chat_template.jinja
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chat_template.jinja
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{%- for message in messages %}
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{%- if message.role == "user" %}
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{{- '<|text_start|>
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' + message.content + '<|text_end|>
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' }}
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{%- elif message.role == "assistant" %}
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{{- '<|corrected_start|>
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' + message.content + '<|corrected_end|>
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' }}
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{%- else %}
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{{- raise('Unknown role: ' + message.role) }}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|corrected_start|>
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' }}
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{%- endif %}
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config.json
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config.json
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{
|
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"architectures": [
|
||||
"Qwen3ForCausalLM"
|
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],
|
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"attention_bias": false,
|
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"attention_dropout": 0.0,
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"chat_template": "{%- for message in messages %}\n{%- if message.role == \"user\" %}\n{{- '<|text_start|>\n' + message.content + '<|text_end|>\n' }}\n{%- elif message.role == \"assistant\" %}\n{{- '<|corrected_start|>\n' + message.content + '<|corrected_end|>\n' }}\n{%- else %}\n{# Raise an error for unsupported roles, as per requirement to remove system message stuff #}\n{{- raise('Unknown role: ' + message.role) }}\n{%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n{{- '<|corrected_start|>\n' }}\n{%- endif %}",
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"eos_token_id": 151643,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 2560,
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"initializer_range": 0.02,
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"intermediate_size": 9728,
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"max_position_embeddings": 32768,
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"max_window_layers": 36,
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"model_type": "qwen3",
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"num_attention_heads": 32,
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"sliding_window": null,
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"tie_word_embeddings": true,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.52.4",
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"unsloth_fixed": true,
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"unsloth_version": "2025.5.9",
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"use_sliding_window": false,
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"vocab_size": 151673
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}
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generation_config.json
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generation_config.json
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{
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"bos_token_id": 151643,
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"pad_token_id": 151654,
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"transformers_version": "4.52.4"
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}
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||||
"model.layers.8.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.norm.weight": "model-00002-of-00002.safetensors"
|
||||
}
|
||||
}
|
||||
46
special_tokens_map.json
Normal file
46
special_tokens_map.json
Normal file
@@ -0,0 +1,46 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
{
|
||||
"content": "<|text_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
{
|
||||
"content": "<|text_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
{
|
||||
"content": "<|corrected_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
{
|
||||
"content": "<|corrected_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:40fd5b853d0598451f720d22bf96c9c4cd4b5c6413cd74d4f5e3494ee990f38d
|
||||
size 11423523
|
||||
263
tokenizer_config.json
Normal file
263
tokenizer_config.json
Normal file
@@ -0,0 +1,263 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151647": {
|
||||
"content": "<|object_ref_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
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|
||||
"rstrip": false,
|
||||
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|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
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|
||||
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|
||||
"rstrip": false,
|
||||
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|
||||
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|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
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|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
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|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
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|
||||
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|
||||
},
|
||||
"151665": {
|
||||
"content": "<tool_response>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
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|
||||
"special": false
|
||||
},
|
||||
"151666": {
|
||||
"content": "</tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151667": {
|
||||
"content": "<think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151668": {
|
||||
"content": "</think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
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|
||||
"special": false
|
||||
},
|
||||
"151669": {
|
||||
"content": "<|text_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151670": {
|
||||
"content": "<|text_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151671": {
|
||||
"content": "<|corrected_start|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151672": {
|
||||
"content": "<|corrected_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|text_start|>",
|
||||
"<|text_end|>",
|
||||
"<|corrected_start|>",
|
||||
"<|corrected_end|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|endoftext|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 32768,
|
||||
"pad_token": "<|vision_pad|>",
|
||||
"padding_side": "right",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user