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Model: pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct Source: Original Platform
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README.md
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---
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license: apache-2.0
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language:
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- hi
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- en
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base_model: openbmb/MiniCPM5-1B
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tags:
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- hindi
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- indic
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- instruction-tuned
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- minicpm5
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- text-generation
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- conversational
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- lora
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- unsloth
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library_name: transformers
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pipeline_tag: text-generation
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---
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# MiniCPM5-1B-Hindi-Instruct
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A Hindi instruction-tuned variant of [openbmb/MiniCPM5-1B](https://huggingface.co/openbmb/MiniCPM5-1B), fine-tuned for Hindi (हिंदी) conversational and instruction-following tasks.
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Part of the [🇮🇳 Hindi LLM Series](https://huggingface.co/collections/pankajpandey-dev) by [@pankajpandey-dev](https://huggingface.co/pankajpandey-dev).
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## Model Details
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- **Base model:** openbmb/MiniCPM5-1B (1.1B parameters)
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- **Language:** Hindi (हिंदी), with English understanding retained from the base
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- **Fine-tuning method:** LoRA (r=32, alpha=64) merged into base weights
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- **Training framework:** [Unsloth](https://github.com/unslothai/unsloth) + TRL
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- **License:** Apache 2.0
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## Training Data
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Fine-tuned on **4,000 high-quality Hindi instruction examples** sampled from:
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- [`ai4bharat/indic-instruct-data-v0.1`](https://huggingface.co/datasets/ai4bharat/indic-instruct-data-v0.1) — `anudesh` (Hindi split): native crowd-sourced Hindi instructions
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- [`ai4bharat/indic-instruct-data-v0.1`](https://huggingface.co/datasets/ai4bharat/indic-instruct-data-v0.1) — `dolly` (Hindi split, filtered to chrF ≥ 60): broad instruction variety
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All examples ≤ 2048 tokens, formatted with the MiniCPM5 ChatML template.
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## Training Configuration
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| Hyperparameter | Value |
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|----------------|-------|
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| LoRA rank | 32 |
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| LoRA alpha | 64 |
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| LoRA dropout | 0.0 |
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| Target modules | q, k, v, o, gate, up, down |
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| Batch size (effective) | 16 |
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| Learning rate | 2e-4 |
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| LR scheduler | cosine |
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| Warmup steps | 15 |
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| Epochs | 2 |
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| Total steps | 500 |
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| Precision | fp16 (4-bit base) |
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| Hardware | NVIDIA Tesla T4 (Colab) |
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| Training time | ~60 minutes |
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| Final training loss | 1.108 |
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## Usage
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### With Transformers
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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model_id = "pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct"
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tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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device_map="auto",
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trust_remote_code=True,
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)
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messages = [
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{"role": "user", "content": "नमस्ते! बारिश के दिन पर एक छोटी कविता लिखो।"}
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]
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inputs = tokenizer.apply_chat_template(
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messages,
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add_generation_prompt=True,
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return_tensors="pt",
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).to(model.device)
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outputs = model.generate(
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inputs,
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max_new_tokens=256,
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temperature=0.7,
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top_p=0.9,
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do_sample=True,
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repetition_penalty=1.1,
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)
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print(tokenizer.decode(outputs[0][inputs.shape[-1]:], skip_special_tokens=True))
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```
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### Recommended Generation Parameters
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- **temperature:** 0.7 (lower = more focused, higher = more creative)
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- **top_p:** 0.9
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- **repetition_penalty:** 1.1
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- **max_new_tokens:** 256–512 depending on task
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### LoRA Adapter Only
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If you prefer to load the LoRA adapter on top of the base model (~85 MB vs 2.2 GB), it's available in the `lora_adapter/` folder of this repo:
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```python
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from peft import PeftModel
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from transformers import AutoModelForCausalLM, AutoTokenizer
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base = AutoModelForCausalLM.from_pretrained("openbmb/MiniCPM5-1B", trust_remote_code=True)
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model = PeftModel.from_pretrained(base, "pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct", subfolder="lora_adapter")
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```
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## Example Outputs
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**Prompt:** बारिश के दिन पर एक छोटी कविता लिखो।
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**Response:** *(creative Hindi poetry generation)*
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**Prompt:** मशीन लर्निंग क्या है? सरल हिंदी में समझाइए।
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**Response:** *(simplified Hindi explanation of ML)*
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**Prompt:** नमस्ते! अपना परिचय दीजिए।
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**Response:** *(conversational Hindi self-introduction)*
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## Quantized Versions (GGUF)
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For running locally with llama.cpp, Ollama, LM Studio, or other GGUF-compatible inference engines.
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## Acknowledgements
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- [OpenBMB](https://huggingface.co/openbmb) for the MiniCPM5-1B base model
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- [AI4Bharat](https://huggingface.co/ai4bharat) (IIT Madras) for the indic-instruct-data dataset
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- [Unsloth](https://github.com/unslothai/unsloth) for the training framework
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## Citation
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If you use this model in your work, please cite:
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```bibtex
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@misc{pandey2026minicpm5hindi,
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title = {MiniCPM5-1B-Hindi-Instruct},
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author = {Pankaj Pandey},
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year = {2026},
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url = {https://huggingface.co/pankajpandey-dev/MiniCPM5-1B-Hindi-Instruct}
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}
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```
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---
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*Part of an ongoing effort to bring strong open-source LLMs to Indian languages. Feedback and contributions welcome via the community tab.*
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179
chat_template.jinja
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{{- bos_token }}{%- if tools %}
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{%- set tool_definitions %}
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{{- "# Tools\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson(ensure_ascii=False) }}
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{%- endfor %}
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{{- '\n</tools>\n\nTool usage guidelines:\n- You may call zero or more functions. If no function calls are needed, just answer normally and do not include any <function ... </function>.\n- When calling a function, return an XML object within <function ... </function> using:\n<function name="function-name"><param name="param-name">param-value</param></function>\n- param-value may be multi-line. If it contains <, & or newline characters, wrap it in a CDATA block: <param name="param-name"><![CDATA[...multi-line value...]]></param>' }}
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{%- endset %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{%- if '<tool_def_sep>' in messages[0].content %}
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{{- messages[0].content.replace('<tool_def_sep>', tool_definitions) }}
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{%- else %}
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{{- messages[0].content + '\n\n' + tool_definitions }}
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{%- endif %}
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{%- else %}
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{{- tool_definitions.lstrip() }}
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{%- endif %}
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{{- '<|im_end|>\n' }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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{%- for message in messages[::-1] %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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{%- set ns.multi_step_tool = false %}
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{%- set ns.last_query_index = index %}
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{%- endif %}
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{%- endfor %}
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{%- for message in messages %}
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{%- if message.content is string %}
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{%- set content = message.content %}
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{%- else %}
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{%- set content = '' %}
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{%- endif %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{%- set reasoning_content = '' %}
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{%- if message.reasoning_content is string %}
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{%- set reasoning_content = message.reasoning_content %}
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{%- else %}
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{%- if '</think>' in content %}
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{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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{%- set content = content.split('</think>')[-1].lstrip('\n') %}
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{%- endif %}
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{%- endif %}
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{%- if message.tool_calls %}
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{%- set content_parts = content.split('<tool_sep>') %}
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{%- set processed_content = content_parts[0] %}
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{%- set tool_calls_count = message.tool_calls|length %}
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{%- set tool_sep_count = content_parts|length - 1 %}
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{%- set min_count = [tool_calls_count, tool_sep_count]|min %}
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{%- for i in range(1, content_parts|length) %}
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{%- set tool_index = i - 1 %}
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{%- if tool_index < tool_calls_count %}
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{%- set tool_call = message.tool_calls[tool_index] %}
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{%- if tool_call.function %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{%- set single_tool_xml %}
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{{- '<function name="' ~ tool_call.name ~ '">' }}
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{%- if tool_call.arguments %}
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{%- set args_dict = tool_call.arguments %}
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{%- for param_name, param_value in args_dict.items() %}
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{{- '<param name="' ~ param_name ~ '">' }}
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{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
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{{- '<![CDATA[' + param_value + ']]>' }}
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{%- else %}
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{{- param_value }}
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{%- endif %}
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{{- '</param>' }}
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{%- endfor %}
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||||
{%- endif %}
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{{- '</function>' }}
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{%- endset %}
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||||
{%- set processed_content = processed_content + single_tool_xml + content_parts[i] %}
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{%- else %}
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||||
{%- set processed_content = processed_content + content_parts[i] %}
|
||||
{%- endif %}
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||||
{%- endfor %}
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|
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{%- if tool_calls_count > tool_sep_count %}
|
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{%- for remaining_index in range(tool_sep_count, tool_calls_count) %}
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{%- set tool_call = message.tool_calls[remaining_index] %}
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||||
{%- if tool_call.function %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{%- set remaining_tool_xml %}
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{{- '<function name="' ~ tool_call.name ~ '">' }}
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{%- if tool_call.arguments %}
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{%- set args_dict = tool_call.arguments %}
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{%- for param_name, param_value in args_dict.items() %}
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{{- '<param name="' ~ param_name ~ '">' }}
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{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
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{{- '<![CDATA[' + param_value + ']]>' }}
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{%- else %}
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{{- param_value }}
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{%- endif %}
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{{- '</param>' }}
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{%- endfor %}
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||||
{%- endif %}
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{{- '</function>' }}
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{%- endset %}
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||||
{%- set processed_content = processed_content + remaining_tool_xml %}
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||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
|
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{%- set content = processed_content %}
|
||||
{%- endif %}
|
||||
|
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{%- if loop.index0 > ns.last_query_index %}
|
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{%- if reasoning_content %}
|
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{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
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{%- else %}
|
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{{- '<|im_start|>' + message.role + '\n' + content }}
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||||
{%- endif %}
|
||||
{%- else %}
|
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{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
|
||||
{%- if message.tool_calls and not has_tool_sep %}
|
||||
{%- for tool_call in message.tool_calls %}
|
||||
{%- if (loop.first and content) or (not loop.first) %}
|
||||
{{- '\n' }}
|
||||
{%- endif %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '<function name="' ~ tool_call.name ~ '">' }}
|
||||
{%- if tool_call.arguments %}
|
||||
{%- set args_dict = tool_call.arguments %}
|
||||
{%- for param_name, param_value in args_dict.items() %}
|
||||
{{- '<param name="' ~ param_name ~ '">' }}
|
||||
{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
|
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{{- '<![CDATA[' + param_value + ']]>' }}
|
||||
{%- else %}
|
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{{- param_value }}
|
||||
{%- endif %}
|
||||
{{- '</param>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '</function>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
||||
{{- '<|im_start|>user' }}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_response>\n' }}
|
||||
{%- if message.content is string %}
|
||||
{{- content }}
|
||||
{%- else %}
|
||||
{{- message.content | tojson(ensure_ascii=False) }}
|
||||
{%- endif %}
|
||||
{{- '\n</tool_response>' }}
|
||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|im_start|>assistant\n' }}
|
||||
{%- if enable_thinking is defined %}
|
||||
{%- if enable_thinking is false %}
|
||||
{{- '<think>\n\n</think>\n\n' }}
|
||||
{%- elif enable_thinking is true %}
|
||||
{{- '<think>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endif %}
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32
config.json
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config.json
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{
|
||||
"architectures": [
|
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"LlamaForCausalLM"
|
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],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 0,
|
||||
"torch_dtype": "float16",
|
||||
"eos_token_id": 1,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 1536,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 4608,
|
||||
"max_position_embeddings": 131072,
|
||||
"mlp_bias": false,
|
||||
"model_type": "llama",
|
||||
"num_attention_heads": 16,
|
||||
"num_hidden_layers": 24,
|
||||
"num_key_value_heads": 2,
|
||||
"pad_token_id": 130559,
|
||||
"pretraining_tp": 1,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_parameters": {
|
||||
"rope_theta": 5000000,
|
||||
"rope_type": "default"
|
||||
},
|
||||
"tie_word_embeddings": false,
|
||||
"unsloth_version": "2026.5.8",
|
||||
"use_cache": false,
|
||||
"vocab_size": 130560
|
||||
}
|
||||
15
generation_config.json
Normal file
15
generation_config.json
Normal file
@@ -0,0 +1,15 @@
|
||||
{
|
||||
"_from_model_config": true,
|
||||
"bos_token_id": 0,
|
||||
"do_sample": true,
|
||||
"eos_token_id": [
|
||||
1,
|
||||
1,
|
||||
130073
|
||||
],
|
||||
"max_length": 131072,
|
||||
"pad_token_id": 130559,
|
||||
"temperature": 0.9,
|
||||
"top_p": 0.95,
|
||||
"transformers_version": "5.5.0"
|
||||
}
|
||||
210
lora_adapter/README.md
Normal file
210
lora_adapter/README.md
Normal file
@@ -0,0 +1,210 @@
|
||||
---
|
||||
base_model: openbmb/MiniCPM5-1B
|
||||
library_name: peft
|
||||
pipeline_tag: text-generation
|
||||
tags:
|
||||
- base_model:adapter:openbmb/MiniCPM5-1B
|
||||
- lora
|
||||
- sft
|
||||
- transformers
|
||||
- trl
|
||||
- unsloth
|
||||
---
|
||||
|
||||
# Model Card for Model ID
|
||||
|
||||
<!-- Provide a quick summary of what the model is/does. -->
|
||||
|
||||
|
||||
|
||||
## Model Details
|
||||
|
||||
### Model Description
|
||||
|
||||
<!-- Provide a longer summary of what this model is. -->
|
||||
|
||||
|
||||
|
||||
- **Developed by:** [More Information Needed]
|
||||
- **Funded by [optional]:** [More Information Needed]
|
||||
- **Shared by [optional]:** [More Information Needed]
|
||||
- **Model type:** [More Information Needed]
|
||||
- **Language(s) (NLP):** [More Information Needed]
|
||||
- **License:** [More Information Needed]
|
||||
- **Finetuned from model [optional]:** [More Information Needed]
|
||||
|
||||
### Model Sources [optional]
|
||||
|
||||
<!-- Provide the basic links for the model. -->
|
||||
|
||||
- **Repository:** [More Information Needed]
|
||||
- **Paper [optional]:** [More Information Needed]
|
||||
- **Demo [optional]:** [More Information Needed]
|
||||
|
||||
## Uses
|
||||
|
||||
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
||||
|
||||
### Direct Use
|
||||
|
||||
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Downstream Use [optional]
|
||||
|
||||
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Out-of-Scope Use
|
||||
|
||||
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Bias, Risks, and Limitations
|
||||
|
||||
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Recommendations
|
||||
|
||||
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
||||
|
||||
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
||||
|
||||
## How to Get Started with the Model
|
||||
|
||||
Use the code below to get started with the model.
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Training Details
|
||||
|
||||
### Training Data
|
||||
|
||||
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Training Procedure
|
||||
|
||||
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
||||
|
||||
#### Preprocessing [optional]
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
|
||||
#### Training Hyperparameters
|
||||
|
||||
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
||||
|
||||
#### Speeds, Sizes, Times [optional]
|
||||
|
||||
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Evaluation
|
||||
|
||||
<!-- This section describes the evaluation protocols and provides the results. -->
|
||||
|
||||
### Testing Data, Factors & Metrics
|
||||
|
||||
#### Testing Data
|
||||
|
||||
<!-- This should link to a Dataset Card if possible. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
#### Factors
|
||||
|
||||
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
#### Metrics
|
||||
|
||||
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Results
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
#### Summary
|
||||
|
||||
|
||||
|
||||
## Model Examination [optional]
|
||||
|
||||
<!-- Relevant interpretability work for the model goes here -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Environmental Impact
|
||||
|
||||
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
||||
|
||||
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
||||
|
||||
- **Hardware Type:** [More Information Needed]
|
||||
- **Hours used:** [More Information Needed]
|
||||
- **Cloud Provider:** [More Information Needed]
|
||||
- **Compute Region:** [More Information Needed]
|
||||
- **Carbon Emitted:** [More Information Needed]
|
||||
|
||||
## Technical Specifications [optional]
|
||||
|
||||
### Model Architecture and Objective
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Compute Infrastructure
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
#### Hardware
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
#### Software
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Citation [optional]
|
||||
|
||||
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
||||
|
||||
**BibTeX:**
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
**APA:**
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Glossary [optional]
|
||||
|
||||
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## More Information [optional]
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Model Card Authors [optional]
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Model Card Contact
|
||||
|
||||
[More Information Needed]
|
||||
### Framework versions
|
||||
|
||||
- PEFT 0.19.1
|
||||
52
lora_adapter/adapter_config.json
Normal file
52
lora_adapter/adapter_config.json
Normal file
@@ -0,0 +1,52 @@
|
||||
{
|
||||
"alora_invocation_tokens": null,
|
||||
"alpha_pattern": {},
|
||||
"arrow_config": null,
|
||||
"auto_mapping": {
|
||||
"base_model_class": "LlamaForCausalLM",
|
||||
"parent_library": "transformers.models.llama.modeling_llama",
|
||||
"unsloth_fixed": true
|
||||
},
|
||||
"base_model_name_or_path": "openbmb/MiniCPM5-1B",
|
||||
"bias": "none",
|
||||
"corda_config": null,
|
||||
"ensure_weight_tying": false,
|
||||
"eva_config": null,
|
||||
"exclude_modules": null,
|
||||
"fan_in_fan_out": false,
|
||||
"inference_mode": true,
|
||||
"init_lora_weights": true,
|
||||
"layer_replication": null,
|
||||
"layers_pattern": null,
|
||||
"layers_to_transform": null,
|
||||
"loftq_config": {},
|
||||
"lora_alpha": 64,
|
||||
"lora_bias": false,
|
||||
"lora_dropout": 0.0,
|
||||
"lora_ga_config": null,
|
||||
"megatron_config": null,
|
||||
"megatron_core": "megatron.core",
|
||||
"modules_to_save": null,
|
||||
"peft_type": "LORA",
|
||||
"peft_version": "0.19.1",
|
||||
"qalora_group_size": 16,
|
||||
"r": 32,
|
||||
"rank_pattern": {},
|
||||
"revision": null,
|
||||
"target_modules": [
|
||||
"up_proj",
|
||||
"gate_proj",
|
||||
"v_proj",
|
||||
"q_proj",
|
||||
"down_proj",
|
||||
"o_proj",
|
||||
"k_proj"
|
||||
],
|
||||
"target_parameters": null,
|
||||
"task_type": "CAUSAL_LM",
|
||||
"trainable_token_indices": null,
|
||||
"use_bdlora": null,
|
||||
"use_dora": false,
|
||||
"use_qalora": false,
|
||||
"use_rslora": false
|
||||
}
|
||||
3
lora_adapter/adapter_model.safetensors
Normal file
3
lora_adapter/adapter_model.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:53872195111263f53a17400aa0257995e8d09f9aed3a6ee96344f8a91782d5cc
|
||||
size 89697856
|
||||
179
lora_adapter/chat_template.jinja
Normal file
179
lora_adapter/chat_template.jinja
Normal file
@@ -0,0 +1,179 @@
|
||||
{{- bos_token }}{%- if tools %}
|
||||
{%- set tool_definitions %}
|
||||
{{- "# Tools\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
|
||||
{%- for tool in tools %}
|
||||
{{- "\n" }}
|
||||
{{- tool | tojson(ensure_ascii=False) }}
|
||||
{%- endfor %}
|
||||
{{- '\n</tools>\n\nTool usage guidelines:\n- You may call zero or more functions. If no function calls are needed, just answer normally and do not include any <function ... </function>.\n- When calling a function, return an XML object within <function ... </function> using:\n<function name="function-name"><param name="param-name">param-value</param></function>\n- param-value may be multi-line. If it contains <, & or newline characters, wrap it in a CDATA block: <param name="param-name"><![CDATA[...multi-line value...]]></param>' }}
|
||||
{%- endset %}
|
||||
|
||||
{{- '<|im_start|>system\n' }}
|
||||
{%- if messages[0].role == 'system' %}
|
||||
{%- if '<tool_def_sep>' in messages[0].content %}
|
||||
{{- messages[0].content.replace('<tool_def_sep>', tool_definitions) }}
|
||||
{%- else %}
|
||||
{{- messages[0].content + '\n\n' + tool_definitions }}
|
||||
{%- endif %}
|
||||
{%- else %}
|
||||
{{- tool_definitions.lstrip() }}
|
||||
{%- endif %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- else %}
|
||||
{%- if messages[0].role == 'system' %}
|
||||
{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
||||
{%- for message in messages[::-1] %}
|
||||
{%- set index = (messages|length - 1) - loop.index0 %}
|
||||
{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
|
||||
{%- set ns.multi_step_tool = false %}
|
||||
{%- set ns.last_query_index = index %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- for message in messages %}
|
||||
{%- if message.content is string %}
|
||||
{%- set content = message.content %}
|
||||
{%- else %}
|
||||
{%- set content = '' %}
|
||||
{%- endif %}
|
||||
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
||||
{%- elif message.role == "assistant" %}
|
||||
{%- set reasoning_content = '' %}
|
||||
{%- if message.reasoning_content is string %}
|
||||
{%- set reasoning_content = message.reasoning_content %}
|
||||
{%- else %}
|
||||
{%- if '</think>' in content %}
|
||||
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
||||
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
|
||||
{%- if message.tool_calls %}
|
||||
{%- set content_parts = content.split('<tool_sep>') %}
|
||||
{%- set processed_content = content_parts[0] %}
|
||||
{%- set tool_calls_count = message.tool_calls|length %}
|
||||
{%- set tool_sep_count = content_parts|length - 1 %}
|
||||
{%- set min_count = [tool_calls_count, tool_sep_count]|min %}
|
||||
|
||||
{%- for i in range(1, content_parts|length) %}
|
||||
{%- set tool_index = i - 1 %}
|
||||
{%- if tool_index < tool_calls_count %}
|
||||
{%- set tool_call = message.tool_calls[tool_index] %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{%- set single_tool_xml %}
|
||||
{{- '<function name="' ~ tool_call.name ~ '">' }}
|
||||
{%- if tool_call.arguments %}
|
||||
{%- set args_dict = tool_call.arguments %}
|
||||
{%- for param_name, param_value in args_dict.items() %}
|
||||
{{- '<param name="' ~ param_name ~ '">' }}
|
||||
{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
|
||||
{{- '<![CDATA[' + param_value + ']]>' }}
|
||||
{%- else %}
|
||||
{{- param_value }}
|
||||
{%- endif %}
|
||||
{{- '</param>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '</function>' }}
|
||||
{%- endset %}
|
||||
{%- set processed_content = processed_content + single_tool_xml + content_parts[i] %}
|
||||
{%- else %}
|
||||
{%- set processed_content = processed_content + content_parts[i] %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
|
||||
{%- if tool_calls_count > tool_sep_count %}
|
||||
{%- for remaining_index in range(tool_sep_count, tool_calls_count) %}
|
||||
{%- set tool_call = message.tool_calls[remaining_index] %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{%- set remaining_tool_xml %}
|
||||
{{- '<function name="' ~ tool_call.name ~ '">' }}
|
||||
{%- if tool_call.arguments %}
|
||||
{%- set args_dict = tool_call.arguments %}
|
||||
{%- for param_name, param_value in args_dict.items() %}
|
||||
{{- '<param name="' ~ param_name ~ '">' }}
|
||||
{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
|
||||
{{- '<![CDATA[' + param_value + ']]>' }}
|
||||
{%- else %}
|
||||
{{- param_value }}
|
||||
{%- endif %}
|
||||
{{- '</param>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '</function>' }}
|
||||
{%- endset %}
|
||||
{%- set processed_content = processed_content + remaining_tool_xml %}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
|
||||
{%- set content = processed_content %}
|
||||
{%- endif %}
|
||||
|
||||
{%- if loop.index0 > ns.last_query_index %}
|
||||
{%- if reasoning_content %}
|
||||
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
|
||||
{%- if message.tool_calls and not has_tool_sep %}
|
||||
{%- for tool_call in message.tool_calls %}
|
||||
{%- if (loop.first and content) or (not loop.first) %}
|
||||
{{- '\n' }}
|
||||
{%- endif %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '<function name="' ~ tool_call.name ~ '">' }}
|
||||
{%- if tool_call.arguments %}
|
||||
{%- set args_dict = tool_call.arguments %}
|
||||
{%- for param_name, param_value in args_dict.items() %}
|
||||
{{- '<param name="' ~ param_name ~ '">' }}
|
||||
{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
|
||||
{{- '<![CDATA[' + param_value + ']]>' }}
|
||||
{%- else %}
|
||||
{{- param_value }}
|
||||
{%- endif %}
|
||||
{{- '</param>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '</function>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
||||
{{- '<|im_start|>user' }}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_response>\n' }}
|
||||
{%- if message.content is string %}
|
||||
{{- content }}
|
||||
{%- else %}
|
||||
{{- message.content | tojson(ensure_ascii=False) }}
|
||||
{%- endif %}
|
||||
{{- '\n</tool_response>' }}
|
||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|im_start|>assistant\n' }}
|
||||
{%- if enable_thinking is defined %}
|
||||
{%- if enable_thinking is false %}
|
||||
{{- '<think>\n\n</think>\n\n' }}
|
||||
{%- elif enable_thinking is true %}
|
||||
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653947
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"model.layers.0.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.1.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.2.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.3.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.4.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.5.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.6.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.7.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.8.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.10.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
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"model.layers.11.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
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"model.layers.12.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.13.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
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"model.layers.14.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.15.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.16.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.17.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.18.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.19.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.20.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.21.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.22.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.layers.23.post_attention_layernorm.weight": "model-00000-of-00001.safetensors",
|
||||
"model.norm.weight": "model-00000-of-00001.safetensors"
|
||||
}
|
||||
}
|
||||
653947
tokenizer.json
Normal file
653947
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
4101
tokenizer_config.json
Normal file
4101
tokenizer_config.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user