Merging stuff to make a potato. Idk about it, might delete later. 

Merge of MiniMerlin via Task arithmetic using mergekit. 
There was no goal except merging. Interest in the outcome tho. I might need to fine-tune it more.

FT on more french data (Merlin). 

Je pense qu'il s'agit du meilleur model français en 3B. Essayez le.

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
import torch

model = AutoModelForCausalLM.from_pretrained(
    "teilomillet/Potato-3B",
    revision="0.1",
    return_dict=True,
    torch_dtype=torch.bfloat16,
    device_map='auto'
)

tokenizer = AutoTokenizer.from_pretrained("teilomillet/Potato-3B")
tokenizer.pad_token = tokenizer.eos_token

text = "[|User|] Comment faire un bon plat ? </s>[|Assistant|]"
inputs = tokenizer(text, return_tensors="pt").to(0)

outputs = model.generate(**inputs, max_new_tokens=800)
print(tokenizer.decode(outputs[0], skip_special_tokens=False))
```



#merge
{"language": ["fr", "en", "zh"], "license": "apache-2.0", "widget": [{"text": "<s> [|User|] Comment faire un bon plat ? </s>[|Assistant|]"}]}
transformers safetensors llama text-generation fr en zh license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us