Description
Phi-4-mini-instruct is a lightweight open model built upon synthetic data and filtered publicly available websites - with a focus on high-quality, reasoning dense data. The model belongs to the Phi-4 model family and supports 128K token context length. The model underwent an enhancement process, incorporating both supervised fine-tuning and direct preference optimization to support precise instruction adherence and robust safety measures.
Imported from https://huggingface.co/unsloth/Phi-4-mini-instruct-GGUF
Predicted Entities
How to use
import sparknlp
from sparknlp.base import *
from sparknlp.annotator import *
from pyspark.ml import Pipeline
document = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
autoGGUFModel = AutoGGUFModel.pretrained("Phi_4_mini_instruct_Q4_K_M_gguf") \
.setInputCols(["document"]) \
.setOutputCol("completions") \
.setBatchSize(4) \
.setNPredict(20) \
.setNGpuLayers(99) \
.setTemperature(0.4) \
.setTopK(40) \
.setTopP(0.9) \
.setPenalizeNl(True)
pipeline = Pipeline().setStages([document, autoGGUFModel])
data = spark.createDataFrame([["Hello, I am a"]]).toDF("text")
result = pipeline.fit(data).transform(data)
result.select("completions").show(truncate = False)
import com.johnsnowlabs.nlp.base._
import com.johnsnowlabs.nlp.annotator._
import org.apache.spark.ml.Pipeline
import spark.implicits._
val document = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val autoGGUFModel = AutoGGUFModel
.pretrained("Phi_4_mini_instruct_Q4_K_M_gguf")
.setInputCols("document")
.setOutputCol("completions")
.setBatchSize(4)
.setNPredict(20)
.setNGpuLayers(99)
.setTemperature(0.4f)
.setTopK(40)
.setTopP(0.9f)
.setPenalizeNl(true)
val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel))
val data = Seq("Hello, I am a").toDF("text")
val result = pipeline.fit(data).transform(data)
result.select("completions").show(truncate = false)
Model Information
| Model Name: | Phi_4_mini_instruct_Q4_K_M_gguf |
| Compatibility: | Spark NLP 6.1.1+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [document] |
| Output Labels: | [completions] |
| Language: | en |
| Size: | 2.5 GB |