README.md

metadata

tags:
  - merge
  - mergekit
  - lazymergekit
  - saucam/Rudra-7b
  - Telugu-LLM-Labs/Indic-gemma-7b-finetuned-sft-Navarasa-2.0
base_model:
  - saucam/Rudra-7b
  - Telugu-LLM-Labs/Indic-gemma-7b-finetuned-sft-Navarasa-2.0

Navrasa-2.0-Rudra-7b-dare-ties

Navrasa-2.0-Rudra-7b-dare-ties is a merge of the following models using LazyMergekit:

• saucam/Rudra-7b
• Telugu-LLM-Labs/Indic-gemma-7b-finetuned-sft-Navarasa-2.0

🧩 Configuration

models:
  - model: saucam/Rudra-7b
    parameters:
      density: 0.5
      weight: 0.4
    # No parameters necessary for base model
  - model: Telugu-LLM-Labs/Indic-gemma-7b-finetuned-sft-Navarasa-2.0
    parameters:
      density: 0.5
      weight: 0.6
merge_method: dare_ties
base_model: Telugu-LLM-Labs/Indic-gemma-7b-finetuned-sft-Navarasa-2.0
parameters:
  int8_mask: true
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "saucam/Navrasa-2.0-Rudra-7b-dare-ties"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])