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="AbacusResearch/haLLAwa")
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AbacusResearch/haLLAwa")
model = AutoModelForCausalLM.from_pretrained("AbacusResearch/haLLAwa")
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haLLAwa

haLLAwa is a merge of the following models using mergekit:

🧩 Configuration

```yaml slices:

  • sources:
    • model: openchat/openchat-3.5-0106 layer_range: [0, 32]
    • model: machinists/Mistral-7B-SQL layer_range: [0, 32]

merge_method: slerp base_model: openchat/openchat-3.5-0106 parameters: t: - filter: self_attn value: [0, 0.5, 0.3, 0.7, 1] - filter: mlp value: [1, 0.5, 0.7, 0.3, 0] - value: 0.5 dtype: bfloat16 ```

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Model size
7B params
Tensor type
BF16
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