[Model] Allow loading from original Mistral format #8168

patrickvonplaten · 2024-09-04T21:29:13Z

Mistral models are usually uploaded in two formats:

The original consolidated format:
consolidated.safetensors
params.json
A bit later the HF format is usually also uploaded:
model-00001-of-00003.safetensors
config.json

This PR allows to load directly from the original consolidated format which should make it easier to directly get new models working in VLLM.

The PR can be tested with:

vllm serve mistralai/Mistral-Nemo-Instruct-2407 --tokenizer_mode mistral --max_model_len 8192 --load_format consolidated

or:

from vllm import LLM, SamplingParams

prompts = [
    "Hello, my name is",
    "The president of the United States is",
    "The capital of France is",
    "The future of AI is",
]
sampling_params = SamplingParams(temperature=0.8, top_p=0.95, seed=0)

model_path = "mistralai/Mistral-7B-Instruct-v0.3"
for model in [model_path]:  # or "mistralai/Mistral-7B-Instruct-v0.3"
    llm = LLM(model=model, tokenizer_mode="mistral", max_model_len=8192, load_format="consolidated")
    outputs = llm.generate(prompts, sampling_params)

    for output in outputs:
        prompt = output.prompt
        generated_text = output.outputs[0].text
        print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}"

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patrickvonplaten · 2024-09-04T23:24:40Z

/ready

mgoin

I think this is reasonable overall but are these consolidated checkpoints going to be actively used going forward?
We tend to want to conform to HF as a standard, so if these checkpoints don't load in transformers now then I think the community will continue to have interest in having those be converted to canonical "HF-style" checkpoints

mgoin · 2024-09-04T23:27:21Z

vllm/model_executor/model_loader/weight_utils.py

    cache_dir: Optional[str],
+    index_file: str,


super nit: I think it makes more sense to have cache_dir after index_file, similar to how hf_hub_download is called

happy to change

mgoin · 2024-09-04T23:33:21Z

vllm/transformers_utils/config.py

@@ -104,6 +110,56 @@ def get_config(
    return config


+def load_params_config(model, revision) -> PretrainedConfig:


Is there a reason why you have this new config? It seems to have the same information you would have in the config.json, just named differently

The main reason is because the original format is always stored in params.json which accompanies the consolidated.safetensors checkpoints.

Guess there are two problems with config.json

They are tied quite heavily to transformers. So if one wants to add a new, no transformers-formatted model it doesn't make too much sense to follow transformers config style

They tend to be quite bloated, e.g. has info that's outdated such as sliding_window here: https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3/blob/e0bc86c23ce5aae1db576c8cca6f06f1f73af2db/config.json#L19

mgoin · 2024-09-04T23:34:12Z

vllm/model_executor/models/llama.py

+    # Mistral/Llama models can also be loaded with --load-format consolidated
+    # from consolidated.safetensors checkpoints
+    consolidated_mapping = {
+        "layers": "model.layers",
+        "attention": "self_attn",
+        "wq": "q_proj",
+        "wk": "k_proj",
+        "wv": "v_proj",
+        "wo": "o_proj",
+        "attention_norm": "input_layernorm",
+        "feed_forward": "mlp",
+        "w1": "gate_proj",
+        "w2": "down_proj",
+        "w3": "up_proj",
+        "ffn_norm": "post_attention_layernorm",
+        "tok_embeddings": "model.embed_tokens",
+        "output": "lm_head",
+        "norm": "model.norm"
+    }


Is this a standard naming scheme used by Llama models as well? I have only seen Mistral models with these style of checkpoints

Yeah the original LLama checkpoints have this naming as well: https://github.com/meta-llama/llama/blob/8fac8befd776bc03242fe7bc2236cdb41b6c609c/llama/model.py#L207

(guess most people use the HF format indeed though)

patrickvonplaten · 2024-09-04T23:55:11Z

I think this is reasonable overall but are these consolidated checkpoints going to be actively used going forward? We tend to want to conform to HF as a standard, so if these checkpoints don't load in transformers now then I think the community will continue to have interest in having those be converted to canonical "HF-style" checkpoints

Hey @mgoin,

Yes at Mistral we usually only release the consolidated checkpoints to begin with (see table here). The community then usually converts the models to transformers but this takes some time and then it takes even more time to wait for the next transformers release. So yes, I think the consolidated format will surely continued to be used!

I understand that it's easier to just conform to HF-style, but I guess VLLM also has GGUF support and it could make sense to start allowing more and more support for other formats? Guess in the future VLLM can run any nn.Module regardless of whether it's in transformers or not no?

The biggest reason why I think it makes sense to allow also for the consolidated format is so that users could have day-0 inference support for Mistral models for future model releases. VLLM is essentially implementing all the model architectures natively in the model register, so it's just about "correctly" loading the file format no? It's a bit painful to have to adapt mistral format to transformers format to allow inference in VLLM. With mistral-common in VLLM and with consolidated.safetensors format loading, models like Mistral-Nemo should be supported out of the box on day 0.

Happy to adapt the PR in a way that fits the design better!

vllm/transformers_utils/config.py

timlacroix · 2024-09-05T06:36:07Z

vllm/config.py

@@ -744,6 +747,7 @@ class LoadFormat(str, enum.Enum):
    SHARDED_STATE = "sharded_state"
    GGUF = "gguf"
    BITSANDBYTES = "bitsandbytes"
+    CONSOLIDATED = "consolidated"


CONSOLIDATED is a bit broad as a name no ? Especially since there is SHARDED_STATE above, I think it could lead to confusion.

Thoughts on LoadFormat.MISTRAL ? This makes it clear that the intent is to have us support / maintain the integration of our models into vLLM.

Yes makes sense!

Changed to "mistral" now - keen to hear what @simon-mo @mgoin think :-)

+1 on calling it "MISTRAL" format

I agree, it's better to be explicit if possible

patrickvonplaten · 2024-09-05T17:02:23Z

Thanks for the feedback @timlacroix @mgoin - think everything should be incorporated. Let me know if there is anything else that should be changed!

mgoin

I appreciate your explanation and justification @patrickvonplaten ! I think this is in a good place, my last gripe is with load_params_config since it would be good to future-proof this for other load formats in the future that may require similar changes. Look in the comments for my proposal

mgoin · 2024-09-05T17:27:00Z

tests/models/test_mistral.py

+    # test that both HF format and mistral format work
+    load_format = "mistral" if model.endswith("v0.3") else "auto"
+
+    with vllm_runner(model,
+                     dtype=dtype,
+                     tokenizer_mode="mistral",
+                     load_format=load_format) as vllm_model:
        vllm_outputs = vllm_model.generate_greedy_logprobs(
            example_prompts, max_tokens, num_logprobs)


I think it would be best if you specifically made a test for "mistralai/Mistral-7B-Instruct-v0.3" where you test the model load with both "safetensors" and "mistral" (and HF to just ensure reference) since both checkpoint formats are present on that model card.

That makes sense! Thanks - will take care of it in a bit

mgoin · 2024-09-05T17:41:06Z

vllm/config.py

+        load_params_config: Load the config from mistral format 
+            (params.json) instead of config.json.


I think you made some good points on supporting checkpoint formats other than HF. Given that assumption, I think it would be best to future-proof the interface of config overrides.

I would like to propose changing this parameter to something like config_format that takes a value from a ConfigFormat enum, defaulting to ConfigFormat.HF_CONFIG or AUTO. Then get_config() can dispatch based on this value to the specified config parsing.

Makes a lot of sense!

vllm/transformers_utils/config.py

vllm/config.py

vllm/transformers_utils/config.py

Co-authored-by: Michael Goin <[email protected]>

…vonplaten/vllm into add_mistral_model_format

mgoin

Thanks for working on getting the CI green, looks like you're close. It does seem like AUTO is causing trouble here, so I would be okay with removing it and defaulting to HF if you can't get it stable. Otherwise this LGTM so we can land when green

patrickvonplaten · 2024-09-06T15:57:55Z

Thanks for working on getting the CI green, looks like you're close. It does seem like AUTO is causing trouble here, so I would be okay with removing it and defaulting to HF if you can't get it stable. Otherwise this LGTM so we can land when green

Yeah I think it should be fine now (CI is all green). GGUF tests were failing because they didn't default to HF. Fixed it and everything should work fine now I believe! Thanks for guiding me through the PR!

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Luu <[email protected]> Date: Tue Sep 3 11:32:27 2024 -0700 [CI] Only PR reviewers/committers can trigger CI on PR (vllm-project#8124) Signed-off-by: kevin <[email protected]> commit bd852f2 Author: Cody Yu <[email protected]> Date: Tue Sep 3 10:49:18 2024 -0700 [Performance] Enable chunked prefill and prefix caching together (vllm-project#8120) Co-authored-by: Tao He <[email protected]> Co-authored-by: Juelianqvq <[email protected]> commit ec26653 Author: Isotr0py <[email protected]> Date: Tue Sep 3 21:37:52 2024 +0800 [Bugfix][VLM] Add fallback to SDPA for ViT model running on CPU backend (vllm-project#8061) commit 0fbc669 Author: Woosuk Kwon <[email protected]> Date: Mon Sep 2 20:35:42 2024 -0700 [Bugfix] Fix single output condition in output processor (vllm-project#7881) commit 6e36f4f Author: wang.yuqi <[email protected]> Date: Tue Sep 3 05:20:12 2024 +0800 improve chunked prefill performance [Bugfix] Fix vllm-project#7592 vllm 0.5.4 enable_chunked_prefill throughput is slightly lower than 0.5.3~0.5.0. (vllm-project#7874) commit dd2a6a8 Author: Isotr0py <[email protected]> Date: Mon Sep 2 23:48:56 2024 +0800 [Bugfix] Fix internlm2 tensor parallel inference (vllm-project#8055) commit 4ca65a9 Author: Isotr0py <[email protected]> Date: Mon Sep 2 20:43:26 2024 +0800 [Core][Bugfix] Accept GGUF model without .gguf extension (vllm-project#8056) commit e2b2aa5 Author: Woosuk Kwon <[email protected]> Date: Sun Sep 1 23:09:46 2024 -0700 [TPU] Align worker index with node boundary (vllm-project#7932) commit e6a26ed Author: Lily Liu <[email protected]> Date: Sun Sep 1 21:23:29 2024 -0700 [SpecDecode][Kernel] Flashinfer Rejection Sampling (vllm-project#7244) commit f8d6014 Author: Shawn Tan <[email protected]> Date: Sun Sep 1 21:37:18 2024 -0400 [Model] Add Granite model (vllm-project#7436) Co-authored-by: Nick Hill <[email protected]> commit 5b86b19 Author: Roger Wang <[email protected]> Date: Sun Sep 1 14:46:57 2024 -0700 [Misc] Optional installation of audio related packages (vllm-project#8063) commit 5231f08 Author: Roger Wang <[email protected]> Date: Sat Aug 31 16:35:53 2024 -0700 [Frontend][VLM] Add support for multiple multi-modal items (vllm-project#8049) commit 8423aef Author: Robert Shaw <[email protected]> Date: Sat Aug 31 15:44:03 2024 -0400 [BugFix][Core] Multistep Fix Crash on Request Cancellation (vllm-project#8059) commit 4f5d844 Author: Nicolò Lucchesi <[email protected]> Date: Sat Aug 31 09:27:58 2024 +0200 [Bugfix] Fix ModelScope models in v0.5.5 (vllm-project#8037) commit d05f0a9 Author: Cyrus Leung <[email protected]> Date: Sat Aug 31 13:26:55 2024 +0800 [Bugfix] Fix import error in Phi-3.5-MoE (vllm-project#8052) commit 622f8ab Author: Pavani Majety <[email protected]> Date: Fri Aug 30 22:18:50 2024 -0700 [Bugfix] bugfix and add model test for flashinfer fp8 kv cache. (vllm-project#8013) commit 1248e85 Author: Wenxiang <[email protected]> Date: Sat Aug 31 03:42:57 2024 +0800 [Model] Adding support for MSFT Phi-3.5-MoE (vllm-project#7729) Co-authored-by: Your Name <[email protected]> Co-authored-by: Zeqi Lin <[email protected]> Co-authored-by: Zeqi Lin <[email protected]> commit 2684efc Author: Woosuk Kwon <[email protected]> Date: Fri Aug 30 09:01:26 2024 -0700 [TPU][Bugfix] Fix tpu type api (vllm-project#8035) commit 058344f Author: Kaunil Dhruv <[email protected]> Date: Fri Aug 30 08:21:02 2024 -0700 [Frontend]-config-cli-args (vllm-project#7737) Co-authored-by: Cyrus Leung <[email protected]> Co-authored-by: Kaunil Dhruv <[email protected]> commit 98cef6a Author: Cyrus Leung <[email protected]> Date: Fri Aug 30 23:20:34 2024 +0800 [Core] Increase default `max_num_batched_tokens` for multimodal models (vllm-project#8028) commit f97be32 Author: Jungho Christopher Cho <[email protected]> Date: Sat Aug 31 00:19:27 2024 +0900 [VLM][Model] TP support for ViTs (vllm-project#7186) Co-authored-by: Roger Wang <[email protected]> Co-authored-by: Roger Wang <[email protected]> commit afd39a4 Author: Cyrus Leung <[email protected]> Date: Fri Aug 30 23:03:28 2024 +0800 [Bugfix] Fix import error in Exaone model (vllm-project#8034) commit 2148441 Author: Richard Liu <[email protected]> Date: Fri Aug 30 00:27:40 2024 -0700 [TPU] Support single and multi-host TPUs on GKE (vllm-project#7613) commit dc13e99 Author: Yohan Na <[email protected]> Date: Fri Aug 30 15:34:20 2024 +0900 [MODEL] add Exaone model support (vllm-project#7819) commit 34a0e96 Author: Avshalom Manevich <[email protected]> Date: Fri Aug 30 11:11:39 2024 +0700 [Kernel] changing fused moe kernel chunk size default to 32k (vllm-project#7995) commit 80c7b08 Author: Woosuk Kwon <[email protected]> Date: Thu Aug 29 19:35:29 2024 -0700 [TPU] Async output processing for TPU (vllm-project#8011) commit 428dd14 Author: afeldman-nm <[email protected]> Date: Thu Aug 29 22:19:08 2024 -0400 [Core] Logprobs support in Multi-step (vllm-project#7652) commit 4abed65 Author: Cyrus Leung <[email protected]> Date: Fri Aug 30 08:49:04 2024 +0800 [VLM] Disallow overflowing `max_model_len` for multimodal models (vllm-project#7998) commit 0c785d3 Author: Wei-Sheng Chin <[email protected]> Date: Thu Aug 29 16:48:11 2024 -0700 Add more percentiles and latencies (vllm-project#7759) commit 4664cea Author: chenqianfzh <[email protected]> Date: Thu Aug 29 16:09:08 2024 -0700 support bitsandbytes 8-bit and FP4 quantized models (vllm-project#7445) commit 257afc3 Author: Harsha vardhan manoj Bikki <[email protected]> Date: Thu Aug 29 13:58:14 2024 -0700 [Neuron] Adding support for context-lenght, token-gen buckets. (vllm-project#7885) Co-authored-by: Harsha Bikki <[email protected]> commit 86a677d Author: Dipika Sikka <[email protected]> Date: Thu Aug 29 16:46:55 2024 -0400 [misc] update tpu int8 to use new vLLM Parameters (vllm-project#7973) commit d78789a Author: Isotr0py <[email protected]> Date: Fri Aug 30 03:54:49 2024 +0800 [Bugfix] Fix incorrect vocal embedding shards for GGUF model in tensor parallelism (vllm-project#7954) commit c334b18 Author: kushanam <[email protected]> Date: Thu Aug 29 12:15:04 2024 -0700 extend cuda graph size for H200 (vllm-project#7894) Co-authored-by: youkaichao <[email protected]> commit 6b34215 Author: Pavani Majety <[email protected]> Date: Thu Aug 29 11:53:11 2024 -0700 [Core][Kernels] Enable FP8 KV Cache with Flashinfer backend. + BugFix for kv_cache_dtype=auto (vllm-project#7985) Co-authored-by: Simon Mo <[email protected]> Co-authored-by: Cody Yu <[email protected]> commit 3f60f22 Author: Alexander Matveev <[email protected]> Date: Thu Aug 29 14:18:26 2024 -0400 [Core] Combine async postprocessor and multi-step (vllm-project#7921) commit f205c09 Author: Jonas M. Kübler <[email protected]> Date: Thu Aug 29 07:18:13 2024 +0200 [Bugfix] Unify rank computation across regular decoding and speculative decoding (vllm-project#7899) commit ef99a78 Author: youkaichao <[email protected]> Date: Wed Aug 28 21:27:06 2024 -0700 Revert "[Core][Kernels] Use FlashInfer backend for FP8 KV Cache when available." (vllm-project#7982) commit 74d5543 Author: Peter Salas <[email protected]> Date: Wed Aug 28 20:24:31 2024 -0700 [VLM][Core] Fix exceptions on ragged NestedTensors (vllm-project#7974) commit a7f65c2 Author: youkaichao <[email protected]> Date: Wed Aug 28 17:32:26 2024 -0700 [torch.compile] remove reset (vllm-project#7975) commit 4289cad Author: Nick Hill <[email protected]> Date: Wed Aug 28 17:22:43 2024 -0700 [Frontend] Minor optimizations to zmq decoupled front-end (vllm-project#7957) Co-authored-by: Robert Shaw <rshaw@neuralmagic> commit af59df0 Author: Michael Goin <[email protected]> Date: Wed Aug 28 19:19:17 2024 -0400 Remove faulty Meta-Llama-3-8B-Instruct-FP8.yaml lm-eval test (vllm-project#7961) commit ce6bf3a Author: youkaichao <[email protected]> Date: Wed Aug 28 16:10:12 2024 -0700 [torch.compile] avoid Dynamo guard evaluation overhead (vllm-project#7898) Co-authored-by: Woosuk Kwon <[email protected]> commit 3cdfe1f Author: bnellnm <[email protected]> Date: Wed Aug 28 18:11:49 2024 -0400 [Bugfix] Make torch registration of punica ops optional (vllm-project#7970) commit fdd9daa Author: Mor Zusman <[email protected]> Date: Thu Aug 29 01:06:52 2024 +0300 [Kernel/Model] Migrate mamba_ssm and causal_conv1d kernels to vLLM (vllm-project#7651) commit 8c56e57 Author: Stas Bekman <[email protected]> Date: Wed Aug 28 13:54:23 2024 -0700 [Doc] fix 404 link (vllm-project#7966) commit eeffde1 Author: Woosuk Kwon <[email protected]> Date: Wed Aug 28 13:10:21 2024 -0700 [TPU] Upgrade PyTorch XLA nightly (vllm-project#7967) commit e5697d1 Author: rasmith <[email protected]> Date: Wed Aug 28 14:37:47 2024 -0500 [Kernel] [Triton] [AMD] Adding Triton implementations awq_dequantize and awq_gemm to support AWQ (vllm-project#7386) commit b98cc28 Author: Pavani Majety <[email protected]> Date: Wed Aug 28 10:01:22 2024 -0700 [Core][Kernels] Use FlashInfer backend for FP8 KV Cache when available. (vllm-project#7798) Co-authored-by: Simon Mo <[email protected]> commit ef9baee Author: Cyrus Leung <[email protected]> Date: Wed Aug 28 23:11:18 2024 +0800 [Bugfix][VLM] Fix incompatibility between vllm-project#7902 and vllm-project#7230 (vllm-project#7948) commit 98c12cf Author: Stas Bekman <[email protected]> Date: Wed Aug 28 05:12:32 2024 -0700 [Doc] fix the autoAWQ example (vllm-project#7937) commit f52a43a Author: youkaichao <[email protected]> Date: Wed Aug 28 01:27:07 2024 -0700 [ci][test] fix pp test failure (vllm-project#7945) commit e358053 Author: Cody Yu <[email protected]> Date: Wed Aug 28 00:36:31 2024 -0700 [Performance] Enable chunked prefill and prefix caching together (vllm-project#7753)

Co-authored-by: Michael Goin <[email protected]>

rosmur · 2024-09-21T19:20:52Z

will this work for pixtral as well?

Co-authored-by: Michael Goin <[email protected]>

Co-authored-by: Michael Goin <[email protected]> Signed-off-by: Alvant <[email protected]>

Co-authored-by: Michael Goin <[email protected]> Signed-off-by: Amit Garg <[email protected]>

ryoungj · 2024-11-14T10:31:47Z

Will this work for the Llama original formats, which, e.g., are in the formats of consolidated.00.pth and params.json?

Co-authored-by: Michael Goin <[email protected]>

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patrickvonplaten changed the title ~~[Mistral model format] Allow loading consolidated model format~~ [Model] Allow loading from original Mistral format Sep 4, 2024

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joerunde mentioned this pull request Sep 11, 2024

[Bugfix] Offline mode fix #8376

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[Model] Allow loading from original Mistral format #8168

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		@@ -104,6 +110,56 @@ def get_config(
		return config


		def load_params_config(model, revision) -> PretrainedConfig:

		load_params_config: Load the config from mistral format
		(params.json) instead of config.json.

[Model] Allow loading from original Mistral format #8168

[Model] Allow loading from original Mistral format #8168

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