Pluto-AI-Labs/Pluto-Genesis-0.6B
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Model: Pluto-AI-Labs/Pluto-Genesis-0.6B
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2026-08-30 01:44:18 +08:00
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---
base_model: Qwen/Qwen3-0.6B
library_name: peft
pipeline_tag: text-generation
tags:
- base_model:adapter:Qwen/Qwen3-0.6B
- lora
- transformers
---
# 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]
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### Model Sources [optional]
<!-- Provide the basic links for the model. -->
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## 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. -->
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### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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### Out-of-Scope Use
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## Bias, Risks, and Limitations
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### Recommendations
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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
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### 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]
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#### 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. -->
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<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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### Results
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#### Summary
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<!-- Relevant interpretability work for the model goes here -->
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## 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]
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## Technical Specifications [optional]
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### Framework versions
- PEFT 0.17.0

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{
"alpha_pattern": {},
"auto_mapping": null,
"base_model_name_or_path": "Qwen/Qwen3-0.6B",
"bias": "none",
"corda_config": null,
"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": {},
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"lora_bias": false,
"lora_dropout": 0.05,
"megatron_config": null,
"megatron_core": "megatron.core",
"modules_to_save": null,
"peft_type": "LORA",
"qalora_group_size": 16,
"r": 64,
"rank_pattern": {},
"revision": null,
"target_modules": [
"q_proj",
"down_proj",
"up_proj",
"k_proj",
"v_proj",
"o_proj",
"gate_proj"
],
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"task_type": "CAUSAL_LM",
"trainable_token_indices": null,
"use_dora": false,
"use_qalora": false,
"use_rslora": false
}

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{%- if messages[0]['role'] == 'system' -%}
{%- set system_message = messages[0]['content'] -%}
{%- set loop_messages = messages[1:] -%}
{%- else -%}
{%- set system_message = 'You are Pluto-Genesis, an advanced AI assistant created by Siddharth N.R. You are a highly capable, thoughtful, and precise assistant that excels at reasoning, mathematics, coding, and general knowledge. You think step-by-step through complex problems and provide clear, accurate, and helpful responses.' -%}
{%- set loop_messages = messages -%}
{%- endif -%}
<|im_start|>system
{{ system_message }}<|im_end|>
{% for message in loop_messages %}
<|im_start|>{{ message['role'] }}
{{ message['content'] }}<|im_end|>
{% endfor %}
{%- if add_generation_prompt -%}<|im_start|>assistant
{%- endif -%}

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