feat(server): Add native support for PEFT Lora models (#762)

- Will detect `peft` model by finding `adapter_config.json`.
- This triggers a totally dedicated `download-weights` path
- This path, loads the adapter config, finds the base model_id
- It loads the base_model
- Then peft_model
- Then `merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.merge_and_unload()`
- Then `save_pretrained(.., safe_serialization=True)
- Add back the config + tokenizer.
- The chosen location is a **local folder with the name of the user
  chosen model id**

PROs:

- Easier than to expect user to merge manually
- Barely any change outside of `download-weights` command.
- This means everything will work in a single load.
- Should enable out of the box SM + HFE

CONs:

- Creates a local merged model in unusual location, potentially
  not saved across docker reloads, or ovewriting some files if the PEFT
  itself was local and containing other files in addition to the lora

Alternatives considered:
- Add `local_files_only=True` every where (discard because of massive
  code change for not a good enough reason)
- Return something to `launcher` about the new model-id (a cleaner
  location for this new model), but it would
  introduce new communication somewhere where we didn't need it before.
- Using the HF cache folder and *stopping* the flow after
  `download-weights` and asking user to restart with the actual local
  model location


Fix #482 


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launcher/src/main.rs

@@ -716,6 +716,11 @@ fn download_convert_model(args: &Args, running: Arc<AtomicBool>) -> Result<(), L
         download_args.push(revision.to_string())
     }
 
+    // Trust remote code for automatic peft fusion
+    if args.trust_remote_code {
+        download_args.push("--trust-remote-code".to_string());
+    }
+
     // Copy current process env
     let mut envs: Vec<(OsString, OsString)> = env::vars_os().collect();
 

server/pyproject.toml

@@ -30,6 +30,7 @@ transformers = "4.29.2"
 einops = "^0.6.1"
 texttable = { version = "^1.6.7", optional = true }
 datasets = { version = "^2.14.0", optional = true }
+peft = "^0.4.0"
 
 [tool.poetry.extras]
 accelerate = ["accelerate"]

server/requirements.txt

 accelerate==0.19.0 ; python_version >= "3.9" and python_version < "4.0"
-aiohttp==3.8.5 ; python_version >= "3.9" and python_version < "4.0"
-aiosignal==1.3.1 ; python_version >= "3.9" and python_version < "4.0"
-async-timeout==4.0.2 ; python_version >= "3.9" and python_version < "4.0"
-attrs==23.1.0 ; python_version >= "3.9" and python_version < "4.0"
 backoff==2.2.1 ; python_version >= "3.9" and python_version < "4.0"
-bitsandbytes==0.38.1 ; python_version >= "3.9" and python_version < "4.0"
 certifi==2023.5.7 ; python_version >= "3.9" and python_version < "4.0"
 charset-normalizer==3.1.0 ; python_version >= "3.9" and python_version < "4.0"
 click==8.1.3 ; python_version >= "3.9" and python_version < "4.0"
-colorama==0.4.6 ; python_version >= "3.9" and python_version < "4.0" and sys_platform == "win32" or python_version >= "3.9" and python_version < "4.0" and platform_system == "Windows"
-datasets==2.14.0 ; python_version >= "3.9" and python_version < "4.0"
+colorama==0.4.6 ; python_version >= "3.9" and python_version < "4.0" and (sys_platform == "win32" or platform_system == "Windows")
 deprecated==1.2.14 ; python_version >= "3.9" and python_version < "4.0"
-dill==0.3.7 ; python_version >= "3.9" and python_version < "4.0"
 einops==0.6.1 ; python_version >= "3.9" and python_version < "4.0"
 filelock==3.12.2 ; python_version >= "3.9" and python_version < "4.0"
-frozenlist==1.4.0 ; python_version >= "3.9" and python_version < "4.0"
 fsspec==2023.6.0 ; python_version >= "3.9" and python_version < "4.0"
-fsspec[http]==2023.6.0 ; python_version >= "3.9" and python_version < "4.0"
 googleapis-common-protos==1.59.1 ; python_version >= "3.9" and python_version < "4.0"
 grpc-interceptor==0.15.2 ; python_version >= "3.9" and python_version < "4.0"
 grpcio-reflection==1.56.0 ; python_version >= "3.9" and python_version < "4.0"
@@ -29,10 +20,8 @@ jinja2==3.1.2 ; python_version >= "3.9" and python_version < "4.0"
 loguru==0.6.0 ; python_version >= "3.9" and python_version < "4.0"
 markupsafe==2.1.3 ; python_version >= "3.9" and python_version < "4.0"
 mpmath==1.3.0 ; python_version >= "3.9" and python_version < "4.0"
-multidict==6.0.4 ; python_version >= "3.9" and python_version < "4.0"
-multiprocess==0.70.15 ; python_version >= "3.9" and python_version < "4.0"
 networkx==3.1 ; python_version >= "3.9" and python_version < "4.0"
-numpy==1.25.0 ; python_version < "4.0" and python_version >= "3.9"
+numpy==1.25.0 ; python_version >= "3.9" and python_version < "4.0"
 opentelemetry-api==1.15.0 ; python_version >= "3.9" and python_version < "4.0"
 opentelemetry-exporter-otlp-proto-grpc==1.15.0 ; python_version >= "3.9" and python_version < "4.0"
 opentelemetry-exporter-otlp-proto-http==1.15.0 ; python_version >= "3.9" and python_version < "4.0"
@@ -43,30 +32,22 @@ opentelemetry-proto==1.15.0 ; python_version >= "3.9" and python_version < "4.0"
 opentelemetry-sdk==1.15.0 ; python_version >= "3.9" and python_version < "4.0"
 opentelemetry-semantic-conventions==0.36b0 ; python_version >= "3.9" and python_version < "4.0"
 packaging==23.1 ; python_version >= "3.9" and python_version < "4.0"
-pandas==2.0.3 ; python_version >= "3.9" and python_version < "4.0"
+peft==0.4.0 ; python_version >= "3.9" and python_version < "4.0"
 protobuf==4.23.3 ; python_version >= "3.9" and python_version < "4.0"
 psutil==5.9.5 ; python_version >= "3.9" and python_version < "4.0"
-pyarrow==12.0.1 ; python_version >= "3.9" and python_version < "4.0"
-python-dateutil==2.8.2 ; python_version >= "3.9" and python_version < "4.0"
-pytz==2023.3 ; python_version >= "3.9" and python_version < "4.0"
 pyyaml==6.0 ; python_version >= "3.9" and python_version < "4.0"
 regex==2023.6.3 ; python_version >= "3.9" and python_version < "4.0"
 requests==2.31.0 ; python_version >= "3.9" and python_version < "4.0"
 safetensors==0.3.1 ; python_version >= "3.9" and python_version < "4.0"
 sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "4.0"
 setuptools==68.0.0 ; python_version >= "3.9" and python_version < "4.0"
-six==1.16.0 ; python_version >= "3.9" and python_version < "4.0"
 sympy==1.12 ; python_version >= "3.9" and python_version < "4.0"
-texttable==1.6.7 ; python_version >= "3.9" and python_version < "4.0"
 tokenizers==0.13.3 ; python_version >= "3.9" and python_version < "4.0"
 torch==2.0.1 ; python_version >= "3.9" and python_version < "4.0"
 tqdm==4.65.0 ; python_version >= "3.9" and python_version < "4.0"
 transformers==4.29.2 ; python_version >= "3.9" and python_version < "4.0"
 typer==0.6.1 ; python_version >= "3.9" and python_version < "4.0"
 typing-extensions==4.7.1 ; python_version >= "3.9" and python_version < "4.0"
-tzdata==2023.3 ; python_version >= "3.9" and python_version < "4.0"
 urllib3==2.0.3 ; python_version >= "3.9" and python_version < "4.0"
 win32-setctime==1.1.0 ; python_version >= "3.9" and python_version < "4.0" and sys_platform == "win32"
 wrapt==1.15.0 ; python_version >= "3.9" and python_version < "4.0"
-xxhash==3.2.0 ; python_version >= "3.9" and python_version < "4.0"
-yarl==1.9.2 ; python_version >= "3.9" and python_version < "4.0"

server/text_generation_server/cli.py

@@ -6,6 +6,7 @@ from pathlib import Path
 from loguru import logger
 from typing import Optional
 from enum import Enum
+from huggingface_hub import hf_hub_download
 
 
 app = typer.Typer()
@@ -88,6 +89,7 @@ def download_weights(
     auto_convert: bool = True,
     logger_level: str = "INFO",
     json_output: bool = False,
+    trust_remote_code: bool = False,
 ):
     # Remove default handler
     logger.remove()
@@ -118,6 +120,12 @@ def download_weights(
     ) is not None
 
     if not is_local_model:
+        try:
+            adapter_config_filename = hf_hub_download(model_id, revision=revision, filename="adapter_config.json")
+            utils.download_and_unload_peft(model_id, revision, trust_remote_code=trust_remote_code)
+        except (utils.LocalEntryNotFoundError, utils.EntryNotFoundError):
+            pass
+
         # Try to download weights from the hub
         try:
             filenames = utils.weight_hub_files(model_id, revision, extension)

server/text_generation_server/models/flash_rw.py

@@ -54,7 +54,7 @@ class FlashRWSharded(FlashCausalLM):
             device,
             dtype,
             process_group=self.process_group,
-            aliases={"transformer.word_embeddings.weight": ["lm_head.weight"]},
+            aliases={"lm_head.weight": ["transformer.word_embeddings.weight"]},
         )
 
         config.quantize = quantize

server/text_generation_server/utils/__init__.py

 from text_generation_server.utils.convert import convert_file, convert_files
 from text_generation_server.utils.dist import initialize_torch_distributed
 from text_generation_server.utils.weights import Weights
+from text_generation_server.utils.peft import download_and_unload_peft
 from text_generation_server.utils.hub import (
     weight_files,
     weight_hub_files,
@@ -26,6 +27,7 @@ __all__ = [
     "weight_files",
     "weight_hub_files",
     "download_weights",
+    "download_and_unload_peft",
     "EntryNotFoundError",
     "HeterogeneousNextTokenChooser",
     "LocalEntryNotFoundError",

server/text_generation_server/utils/peft.py

+import os
+import json
+from loguru import logger
+import torch
+
+from transformers import AutoTokenizer
+from peft import AutoPeftModelForCausalLM, AutoPeftModelForSeq2SeqLM
+
+def download_and_unload_peft(model_id, revision, trust_remote_code):
+    torch_dtype = torch.float16
+
+    logger.info("Peft model detected.")
+    logger.info("Loading the model it might take a while without feedback")
+    try:
+        model = AutoPeftModelForCausalLM.from_pretrained(
+            model_id,
+            revision=revision,
+            torch_dtype=torch_dtype,
+            trust_remote_code=trust_remote_code,
+            low_cpu_mem_usage=True,
+        )
+    except Exception:
+        model = AutoPeftModelForSeq2SeqLM.from_pretrained(
+            model_id,
+            revision=revision,
+            torch_dtype=torch_dtype,
+            trust_remote_code=trust_remote_code,
+            low_cpu_mem_usage=True,
+        )
+    logger.info(f"Loaded.")
+    logger.info(f"Merging the lora weights.")
+
+    base_model_id = model.peft_config["default"].base_model_name_or_path
+
+    model = model.merge_and_unload()
+    
+    os.makedirs(model_id, exist_ok=True)
+    cache_dir = model_id
+    logger.info(f"Saving the newly created merged model to {cache_dir}")
+    tokenizer = AutoTokenizer.from_pretrained(base_model_id)
+    model.save_pretrained(cache_dir, safe_serialization=True)
+    model.config.save_pretrained(cache_dir)
+    tokenizer.save_pretrained(cache_dir)
+
+
+