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="nwhamed/trail")
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("nwhamed/trail")
model = AutoModelForCausalLM.from_pretrained("nwhamed/trail")
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trail

trail is a merge of the following models using mergekit:

🧩 Configuration

    "models": [
      {
        "model": "yam-peleg/Experiment26-7B",
        "parameters": {}
      },
      {
        "model": "chihoonlee10/T3Q-Mistral-Orca-Math-DPO",
        "parameters": {
          "density": 0.53,
          "weight": 0.6
        }
      }
    ],
    "merge_method": "dare_ties",
    "base_model": "yam-peleg/Experiment26-7B",
    "parameters": {
      "int8_mask": true,
      "dtype": "bfloat16",
      "random_seed": 0
    }
  }
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