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Model: niljen/xearnes-phi4-mini
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---
base_model: microsoft/Phi-4-mini-instruct
library_name: peft
pipeline_tag: text-generation
tags:
- base_model:adapter:microsoft/Phi-4-mini-instruct
- lora
- sft
- transformers
- trl
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
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- **Developed by:** [More Information Needed]
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## Uses
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### Direct Use
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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.
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## Training Details
### Training Data
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### Training Procedure
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#### Preprocessing [optional]
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#### Training Hyperparameters
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#### Summary
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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 0.20.0

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"alora_invocation_tokens": null,
"alpha_pattern": {},
"arrow_config": null,
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"base_model_name_or_path": "microsoft/Phi-4-mini-instruct",
"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,
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"loftq_config": {},
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"lora_bias": false,
"lora_dropout": 0,
"lora_ga_config": null,
"megatron_config": null,
"megatron_core": "megatron.core",
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"r": 16,
"rank_pattern": {},
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"target_modules": [
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"k_proj",
"v_proj",
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"task_type": "CAUSAL_LM",
"trainable_token_indices": null,
"use_bdlora": null,
"use_dora": false,
"use_qalora": false,
"use_rslora": false,
"velora_config": null
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{% for message in messages %}{% if message['role'] == 'system' and 'tools' in message and message['tools'] is not none %}{{ '<|' + message['role'] + '|>' + message['content'] + '<|tool|>' + message['tools'] + '<|/tool|>' + '<|end|>' }}{% else %}{{ '<|' + message['role'] + '|>' + message['content'] + '<|end|>' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>' }}{% else %}{{ eos_token }}{% endif %}

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{
"add_prefix_space": false,
"backend": "tokenizers",
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"eos_token": "<|endoftext|>",
"is_local": false,
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"unk_token": "<|endoftext|>"
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