Text-generation-inference: "You are using a model of type llama to instantiate a model of type ."
I’m trying to run the Docker container but encountering the errorYou are using a model of type llama to instantiate a model of type . This is not supported for all configurations of models and can yield errors.during the “Warming up model” part and after  allocating 11GB of GPU memory.I tried adding-e GPTQ_BITS=4 -e GPTQ_GROUPSIZE=128but that made no difference. I also did my research and read almost every issue on the repo but I don’t think this problem has been encountered before.Also tried addingDISABLE_EXLLAMA=Trueand--disable-custom-kernelsDocker Commandsudo docker run --gpus all --shm-size 16g -p 8183:80 \
        --runtime=nvidia \
        -v /storage/text-generation-inference/docker/data:/data ghcr.io/huggingface/text-generation-inference:latest \
        --model-id TheBloke/MythoMax-L2-13B-GPTQ --revision gptq-4bit-128g-actorder_True \
        --quantize gptqVersion:ghcr.io/huggingface/text-generation-inference:latestModel:TheBloke/MythoMax-L2-13B-GPTQ:gptq-4bit-128g-actorder_TrueGPU: Nvidia A4000Ubuntu 22.04LogsCommand Ouput2023-08-26T23:55:35.854791Z  INFO text_generation_launcher: Args { model_id: "TheBloke/MythoMax-L2-13B-GPTQ", revision: Some("gptq-4bit-128g-actorder_True"), validation_workers: 2, sharded: None, num_shard: Some(1), quantize: Some(Gptq), dtype: None, trust_remote_code: false, max_concurrent_requests: 128, max_best_of: 2, max_stop_sequences: 4, max_input_length: 1024, max_total_tokens: 2048, waiting_served_ratio: 1.2, max_batch_prefill_tokens: 4096, max_batch_total_tokens: None, max_waiting_tokens: 20, hostname: "9f8054981ef0", port: 80, shard_uds_path: "/tmp/text-generation-server", master_addr: "localhost", master_port: 29500, huggingface_hub_cache: Some("/data"), weights_cache_override: None, disable_custom_kernels: false, cuda_memory_fraction: 1.0, rope_scaling: None, rope_factor: None, json_output: false, otlp_endpoint: None, cors_allow_origin: [], watermark_gamma: None, watermark_delta: None, ngrok: false, ngrok_authtoken: None, ngrok_edge: None, env: false }
2023-08-26T23:55:35.855120Z  INFO download: text_generation_launcher: Starting download process.
2023-08-26T23:55:42.115911Z  INFO text_generation_launcher: Files are already present on the host. Skipping download.

2023-08-26T23:55:42.966478Z  INFO download: text_generation_launcher: Successfully downloaded weights.
2023-08-26T23:55:42.967019Z  INFO shard-manager: text_generation_launcher: Starting shard rank=0
2023-08-26T23:55:50.341447Z  INFO text_generation_launcher: Using exllama kernels

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2023-08-26T23:55:52.991872Z  INFO shard-manager: text_generation_launcher: Waiting for shard to be ready... rank=0
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2023-08-26T23:55:57.879732Z  INFO text_generation_launcher: Server started at unix:///tmp/text-generation-server-0

2023-08-26T23:55:57.900250Z  INFO shard-manager: text_generation_launcher: Shard ready in 14.931675025s rank=0
2023-08-26T23:55:57.987600Z  INFO text_generation_launcher: Starting Webserver
2023-08-26T23:55:59.443055Z  INFO text_generation_router: router/src/main.rs:367: Serving revision 48caaecfc0ca83f44d056a3f46d4c1661bbea1e7 of model TheBloke/MythoMax-L2-13B-GPTQ
2023-08-26T23:55:59.452758Z  INFO text_generation_router: router/src/main.rs:210: Warming up model
2023-08-26T23:56:11.299165Z ERROR warmup{max_input_length=1024 max_prefill_tokens=4096}:warmup: text_generation_client: router/client/src/lib.rs:33: Server error: transport error
Error: Warmup(Generation("transport error"))
2023-08-26T23:56:11.411063Z ERROR text_generation_launcher: Webserver Crashed
2023-08-26T23:56:11.411132Z  INFO text_generation_launcher: Shutting down shards
2023-08-26T23:56:11.424793Z ERROR shard-manager: text_generation_launcher: Shard complete standard error output:

You are using a model of type llama to instantiate a model of type . This is not supported for all configurations of models and can yield errors. rank=0
2023-08-26T23:56:11.424860Z ERROR shard-manager: text_generation_launcher: Shard process was signaled to shutdown with signal 4 rank=0Sometimes I don’t get theShard complete standard error outputmessage.
2023-09-04T10:14:01Z
Did you find any solution to this? I try deploying models on sagemaker, with the code provided on huggingface.It always fails. For example:Llama-2-7b-german-assistant-v3-4bit-autogptqI noticed it happens with the gptq models
2023-09-09T15:53:48Z
i have same issue,File “/opt/conda/lib/python3.9/site-packages/text_generation_server/utils/weights.py”, line 49, in get_filenameraise RuntimeError(f"weight {tensor_name} does not exist")RuntimeError: weight model.layers.0.self_attn.rotary_emb.inv_freq does not existYou are using a model of type llama to instantiate a model of type .I am trying to deploy Phind/Phind-CodeLlama-34B-v2
2023-09-14T21:31:43Z
I’m getting this same error about theinv_freqweight not existing.For reference I am attempting to deploycodellama/CodeLlama-7b-hfon Sagemaker using the DLC inference container viaHuggingFaceModel().I found this thread in the TGI repoCannot load LLaMA models saved with latest transformers · Issue #790 · huggingface/text-generation-inference · GitHub. Not sure how we can apply that change to our situation (deploying from Sagemaker).Any ideas are appreciated!
2023-10-18T14:01:53Z
Up! Facing the same issue!
2023-11-03T08:17:15Z
same issue here, trying to deploy finetuned meta-llama/Llama-2-7b-chat-hf with image_uri= get_huggingface_llm_image_uri(“huggingface”,version=“0.9.3”) on sagemaker