How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="ameykaran/DilLeiX-it")
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ameykaran/DilLeiX-it")
model = AutoModelForCausalLM.from_pretrained("ameykaran/DilLeiX-it", device_map="auto")
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Configuration Parsing Warning:In config.json: "num_experts_per_tok" must be a number

DilLeiX-instruction-tuned Model

An indic-multilingual small language model (~150M parameters) capable of understanding English, Hindi and Mizo. It is finetuned on Humour detection and Temporal reasoning tasks.

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Model size
81.7M params
Tensor type
F32
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