Add LongCat-Flash

[molbap]

What does this PR do?

As per title, adds support for LongCat-Flash, a 560B MoE from Meituan.

Status:

• Current modeling_longcat_flash file allows loading checkpoint without trust_remote_code, using a specific base_model_tp_plan found in the config. `from_pretrained('..., tp_plan='auto') loads the model properly.
• Chat template is as provided by authors.
• A no-op hook added to deepseek_v3 to abstract lora scaling.
• Testing out generations and correctness. # DOING
• A few modular adjustments to make to derive from DeepSeekv3, estimate ~300 loc total.
• Quality & last touches

Launch snippet:

# launch_longcat.py
from transformers import LongcatFlashForCausalLM, AutoTokenizer
import torch

torch.manual_seed(30)
model_id = "meituan-longcat/LongCat-Flash-Chat"

tokenizer = AutoTokenizer.from_pretrained(model_id)

chat = [
      {"role": "user", "content": "Hello! What is the capital of France? What can you tell me about it?"},
]

model = LongcatFlashForCausalLM.from_pretrained(
      model_id,
      tp_plan="auto",
      dtype=torch.bfloat16,
      trust_remote_code=False, # can be removed.
      )

inputs = tokenizer.apply_chat_template(
      chat, tokenize=True, add_generation_prompt=True, return_tensors="pt").to(model.device)

outputs = model.generate(inputs, max_new_tokens=30)
print(tokenizer.batch_decode(outputs))

Note that you will need at least 2x8 H100 to launch the model with TP as follows

torchrun  --nproc_per_node=8 --nnodes=2 --node_rank=0 | 1  --rdzv-id <an_id> --rdzv-backend c10d --rdzv-endpoint $NODE_ID:$NODE_PORT  --log-dir ./logs_longcat launch_longcat.py

[github-actions]

[For maintainers] Suggested jobs to run (before merge)

run-slow: deepseek_v3

[HuggingFaceDocBuilderDev]

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