Compare model versions

Diff

Before

Not present in the earlier snapshot.

After

The original FP32 QAD source checkpoint is available in
[`qad/`](https://huggingface.co/LiquidAI/LFM2.5-350M-GGUF/tree/main/qad), with its model config,
tokenizer, generation defaults, and the same chat template as the released QAD GGUF.
It can be loaded in Transformers by passing `subfolder="qad"`:

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

repo_id = "LiquidAI/LFM2.5-350M-GGUF"
tokenizer = AutoTokenizer.from_pretrained(repo_id, subfolder="qad")
model = AutoModelForCausalLM.from_pretrained(
    repo_id, subfolder="qad", dtype="auto", device_map="auto"
)

inputs = tokenizer.apply_chat_template(
    [{"role": "user", "content": "What is 2 + 2?"}],
    tokenize=True, add_generation_prompt=True, return_dict=True, return_tensors="pt",
).to(model.device)
outputs = model.generate(**inputs, max_new_tokens=128)
print(tokenizer.decode(outputs[0, inputs["input_ids"].shape[-1]:], skip_special_tokens=True))
```

These weights are intended for fine-tuning and experimentation. Published QAD
results apply to the Q4_0 GGUF; direct FP32/BF16 inference and other quantization
formats may behave differently. See the [source checkpoint documentation](qad/README.md)
for validation details and the license.