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Model: Kortix/FastApply-1.5B-v1.0 Source: Original Platform
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README.md
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---
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base_model: unsloth/qwen2.5-coder-1.5b-instruct-bnb-4bit
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language:
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- en
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license: apache-2.0
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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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- qwen2
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- trl
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- sft
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- fast-apply
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- instant-apply
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---
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# FastApply-1.5B-v1.0
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[Github: kortix-ai/fast-apply](https://github.com/kortix-ai/fast-apply)
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[Dataset: Kortix/FastApply-dataset-v1.0](https://huggingface.co/datasets/Kortix/FastApply-dataset-v1.0)
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[Try it now on 👉 Google Colab](https://colab.research.google.com/drive/1BNCab4oK-xBqwFQD4kCcjKc7BPKivkm1?usp=sharing)
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## Model Details
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### Basic Information
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- **Developed by:** Kortix
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- **License:** apache-2.0
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- **Finetuned from model:** [unsloth/Qwen2.5-Coder-1.5B-Instruct-bnb-4bit](https://huggingface.co/unsloth/Qwen2.5-Coder-1.5B-Instruct-bnb-4bit)
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### Model Description
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FastApply-1.5B-v1.0 is a 1.5B model designed for instant code application, producing full file edits to power [SoftGen AI](https://softgen.ai/).
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It is part of the Fast Apply pipeline for data generation and fine-tuning Qwen2.5 Coder models.
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The model achieves high throughput when deployed on fast providers like Fireworks while maintaining high edit accuracy, with a speed of approximately 340 tokens/second.
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## Intended Use
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FastApply-1.5B-v1.0 is intended for use in AI-powered code editors and tools that require fast, accurate code modifications. It is particularly well-suited for:
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- Instant code application tasks
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- Full file edits
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- Integration with AI-powered code editors like Aider and PearAI
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- Local tools to reduce the cost of frontier model output
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## Inference template
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FastApply-1.5B-v1.0 is based on the Qwen2.5 Coder architecture and is fine-tuned for code editing tasks. It uses a specific prompt structure for inference:
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```
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<|im_start|>system
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You are a coding assistant that helps merge code updates, ensuring every modification is fully integrated.<|im_end|>
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<|im_start|>user
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Merge all changes from the <update> snippet into the <code> below.
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- Preserve the code's structure, order, comments, and indentation exactly.
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- Output only the updated code, enclosed within <updated-code> and </updated-code> tags.
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- Do not include any additional text, explanations, placeholders, ellipses, or code fences.
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<code>{original_code}</code>
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<update>{update_snippet}</update>
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Provide the complete updated code.<|im_end|>
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<|im_start|>assistant
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```
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The model's output is structured as:
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```
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<updated-code>[Full-complete updated file]</updated-code>
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```
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## Additional Information
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For more details on the Fast Apply pipeline, data generation process, and deployment instructions, please refer to the [GitHub repository](https://github.com/kortix-ai/fast-apply).
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## How to Use
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To use the model, you can load it using the Hugging Face Transformers library:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("Kortix/FastApply-1.5B-v1.0", device_map="auto")
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tokenizer = AutoTokenizer.from_pretrained("Kortix/FastApply-1.5B-v1.0")
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# Prepare your input following the prompt structure mentioned above
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input_text = """<|im_start|>system
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You are a coding assistant that helps merge code updates, ensuring every modification is fully integrated.<|im_end|>
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<|im_start|>user
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Merge all changes from the <update> snippet into the <code> below.
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- Preserve the code's structure, order, comments, and indentation exactly.
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- Output only the updated code, enclosed within <updated-code> and </updated-code> tags.
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- Do not include any additional text, explanations, placeholders, ellipses, or code fences.
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<code>{original_code}</code>
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<update>{update_snippet}</update>
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Provide the complete updated code.<|im_end|>
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<|im_start|>assistant
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"""
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input_text = input_text.format(
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original_code=original_code,
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update_snippet=update_snippet,
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).strip()
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# Generate the response
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input_ids = tokenizer.encode(input_text, return_tensors="pt")
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output = model.generate(input_ids, max_length=8192,)
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response = tokenizer.decode(output[0][len(input_ids[0]):])
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print(response)
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# Extract the updated code from the response
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updated_code = response.split("<updated-code>")[1].split("</updated-code>")[0]
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```
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## Evaluation:
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}
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config.json
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{
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"_name_or_path": "unsloth/Qwen2.5-Coder-1.5B-Instruct-bnb-4bit",
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"eos_token_id": 151643,
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"hidden_act": "silu",
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"hidden_size": 1536,
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"initializer_range": 0.02,
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"intermediate_size": 8960,
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"max_position_embeddings": 32768,
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"max_window_layers": 21,
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"model_type": "qwen2",
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"num_attention_heads": 12,
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"num_hidden_layers": 28,
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"tie_word_embeddings": true,
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"transformers_version": "4.44.2",
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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{
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"repetition_penalty": 1.1,
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"temperature": 0.7,
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"top_k": 20,
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"top_p": 0.8,
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"transformers_version": "4.44.2"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 3087467144
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{
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"additional_special_tokens": [
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"<|im_start|>",
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"<|im_end|>",
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"<|object_ref_start|>",
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"<|object_ref_end|>",
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"<|box_start|>",
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"<|box_end|>",
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"<|quad_end|>",
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"<|vision_start|>",
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"<|video_pad|>"
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"pad_token": {
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"content": "<|PAD_TOKEN|>",
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"single_word": false
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}
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{
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"add_bos_token": false,
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"add_prefix_space": false,
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"151643": {
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"single_word": false,
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"151651": {
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"151652": {
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"content": "<|vision_start|>",
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"lstrip": false,
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"single_word": false,
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"special": true
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},
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"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,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151655": {
|
||||||
|
"content": "<|image_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151656": {
|
||||||
|
"content": "<|video_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151657": {
|
||||||
|
"content": "<tool_call>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151658": {
|
||||||
|
"content": "</tool_call>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"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|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151663": {
|
||||||
|
"content": "<|repo_name|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151664": {
|
||||||
|
"content": "<|file_sep|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151665": {
|
||||||
|
"content": "<|PAD_TOKEN|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"additional_special_tokens": [
|
||||||
|
"<|im_start|>",
|
||||||
|
"<|im_end|>",
|
||||||
|
"<|object_ref_start|>",
|
||||||
|
"<|object_ref_end|>",
|
||||||
|
"<|box_start|>",
|
||||||
|
"<|box_end|>",
|
||||||
|
"<|quad_start|>",
|
||||||
|
"<|quad_end|>",
|
||||||
|
"<|vision_start|>",
|
||||||
|
"<|vision_end|>",
|
||||||
|
"<|vision_pad|>",
|
||||||
|
"<|image_pad|>",
|
||||||
|
"<|video_pad|>"
|
||||||
|
],
|
||||||
|
"bos_token": null,
|
||||||
|
"chat_template": "{%- if messages[0]['role'] == 'system' %} \n {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }} \n {%- else %} \n {{- '<|im_start|>system\nYou are a coding assistant that helps merge code updates, ensuring every modification is fully integrated.<|im_end|>\n' }} \n {%- endif %} \n {%- for message in messages %} \n {%- if message.role in ['user', 'assistant'] or (message.role == 'system' and not loop.first) %} \n {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>\n' }} \n {%- endif %} \n {%- endfor %} \n {%- if add_generation_prompt %} \n {{- '<|im_start|>assistant\n' }} \n {%- endif %}",
|
||||||
|
"clean_up_tokenization_spaces": false,
|
||||||
|
"eos_token": "<|im_end|>",
|
||||||
|
"errors": "replace",
|
||||||
|
"model_max_length": 32768,
|
||||||
|
"pad_token": "<|PAD_TOKEN|>",
|
||||||
|
"padding_side": "left",
|
||||||
|
"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