1. 17 Apr, 2024 1 commit
  2. 12 Apr, 2024 2 commits
    • Nicolas Patry's avatar
      Improve the defaults for the launcher (#1727) · 1b2670c8
      Nicolas Patry authored
      # What does this PR do?
      
      - Renamed `max_input_length` into `max_input_tokens` for consistency
      (backward compatible change, will yell if both are set.)
      - Will now use the config for `max_input_tokens` `max_total_token` and
      `max_batch_total_tokens`.
      - Capping the values to 16k in order to save VRAM on behalf of users
      (overriddable by simply setting the values).
      
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      1b2670c8
    • Nicolas Patry's avatar
      Fp8 Support (#1726) · 408dbc48
      Nicolas Patry authored
      # What does this PR do?
      
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      408dbc48
  3. 11 Apr, 2024 3 commits
  4. 10 Apr, 2024 1 commit
  5. 08 Apr, 2024 1 commit
  6. 04 Apr, 2024 1 commit
    • Nicolas Patry's avatar
      Add cuda graphs sizes and make it default. (#1703) · 99874eae
      Nicolas Patry authored
      # What does this PR do?
      
      ```
      text-generation-launcher --model-id XXX # Uses cuda graphs by default
      text-generation-launcher --model-id XXX --cuda-graphs "1,2"  #Restrict the number of cuda graphs which saves VRAM
      text-generation-launcher --model-id XXX --cuda-graphs "0"  # Disabling it entirely
      ```
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      99874eae
  7. 29 Mar, 2024 1 commit
  8. 15 Feb, 2024 1 commit
    • drbh's avatar
      Outlines guided generation (#1539) · cef0553d
      drbh authored
      This WIP PR starts to add grammar support via outlines, currently this
      PR supports very simple regex grammars and does not optimize for
      precompiling or caching grammar fsm's.
      
      todo:
      - [X] add simple outlines guidance to `NextTokenChooser`
      - [X] update protos for grammar
      - [X] update generation params API
      - [X] constrain simple grammar
      - [ ] support parsing more complex grammar into fsm
      - [ ] support all outline support grammar types
      - [ ] explore optimizations to avoid recompiling grammars
      
      guided request
      ```bash
      curl -s 'http://localhost:3000/generate' \
      --header 'Content-Type: application/json' \
      --data-raw '{
          "inputs": "make an email for david: \n",
          "parameters": {
              "max_new_tokens": 6,
              "grammar": "[\\w-]+@([\\w-]+\\.)+[\\w-]+"
          }
      }' | jq
      ```
      response
      ```json
      {
        "generated_text": "david@example.com"
      }
      ```
      
      unguided request
      ```bash
      curl -s 'http://localhost:3000/generate' \
      --header 'Content-Type: application/json' \
      --data '{
          "inputs": "make an email for david: \n",
          "parameters": {
              "max_new_tokens": 6
          }
      }' | jq
      ```
      response
      ```json
      {
        "generated_text": "    email = 'david"
      }
      ```
      cef0553d
  9. 12 Feb, 2024 1 commit
  10. 09 Feb, 2024 1 commit
  11. 29 Jan, 2024 1 commit
    • Nicolas Patry's avatar
      Create the compute type at launch time (if not provided in the env). (#1505) · a9ea6068
      Nicolas Patry authored
      # What does this PR do?
      
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      a9ea6068
  12. 26 Jan, 2024 2 commits
  13. 25 Jan, 2024 1 commit
  14. 22 Jan, 2024 1 commit
  15. 11 Dec, 2023 1 commit
  16. 27 Sep, 2023 1 commit
    • Nicolas Patry's avatar
      Support eetq weight only quantization (#1068) · 95a4bb69
      Nicolas Patry authored
      # What does this PR do?
      
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      95a4bb69
  17. 25 Sep, 2023 1 commit
    • Nicolas Patry's avatar
      Add AWQ quantization inference support (#1019) (#1054) · c5de7cd8
      Nicolas Patry authored
      # Add AWQ quantization inference support
      
      Fixes
      https://github.com/huggingface/text-generation-inference/issues/781
      
      This PR (partially) adds support for AWQ quantization for inference.
      More information on AWQ [here](https://arxiv.org/abs/2306.00978). In
      general, AWQ is faster and more accurate than GPTQ, which is currently
      supported by TGI.
      
      This PR installs 4-bit GEMM custom CUDA kernels released by AWQ authors
      (in `requirements.txt`, just one line change).
      
      Quick way to test this PR would be bring up TGI as follows:
      
      ```
      text-generation-server download-weights abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq
      
      text-generation-launcher \
      --huggingface-hub-cache ~/.cache/huggingface/hub/ \
      --model-id abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq \
      --trust-remote-code --port 8080 \
      --max-input-length 2048 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 \
      --quantize awq
      ```
      
      Please note:
      * This PR was tested with FlashAttention v2 and vLLM.
      * This PR adds support for AWQ inference, not quantizing the models.
      That needs to be done outside of TGI, instructions
      
      [here](https://github.com/mit-han-lab/llm-awq/tree/f084f40bd996f3cf3a0633c1ad7d9d476c318aaa).
      * This PR only adds support for `FlashLlama` models for now.
      * Multi-GPU setup has not been tested. 
      * No integration tests have been added so far, will add later if
      maintainers are interested in this change.
      * This PR can be tested on any of the models released
      
      [here](https://huggingface.co/abhinavkulkarni?sort_models=downloads#models).
      
      Please refer to the linked issue for benchmarks for
      
      [abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq](https://huggingface.co/abhinavkulkarni/meta-llama-Llama-2-7b-chat-hf-w4-g128-awq)
      vs
      
      [TheBloke/Llama-2-7b-Chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-7b-Chat-GPTQ).
      
      Please note, AWQ has released faster (and in case of Llama, fused)
      kernels for 4-bit GEMM, currently at the top of the `main` branch at
      https://github.com/mit-han-lab/llm-awq, but this PR uses an older commit
      that has been tested to work. We can switch to latest commit later on.
      
      ## Who can review?
      
      @OlivierDehaene OR @Narsil
      
      ---------
      
      
      
      # What does this PR do?
      
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      ---------
      Co-authored-by: default avatarAbhinav M Kulkarni <abhinavkulkarni@gmail.com>
      Co-authored-by: default avatarAbhinav Kulkarni <abhinav@concentric.ai>
      c5de7cd8
  18. 28 Aug, 2023 1 commit
    • Nicolas Patry's avatar
      Rebased #617 (#868) · 211b54ac
      Nicolas Patry authored
      # What does this PR do?
      
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      ---------
      Co-authored-by: default avatarVincent Brouwers <vincent.brouwers@ing.com>
      211b54ac
  19. 03 Aug, 2023 2 commits
    • Nicolas Patry's avatar
      Merge BNB 4bit. (#770) · 16fadcec
      Nicolas Patry authored
      # What does this PR do?
      
      
      See #626 
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      16fadcec
    • Nicolas Patry's avatar
      feat(server): Add native support for PEFT Lora models (#762) · ac736fd8
      Nicolas Patry authored
      - 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 
      
      
      # What does this PR do?
      
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      ac736fd8
  20. 31 Jul, 2023 1 commit
    • Nicolas Patry's avatar
      Adding Rope scaling. (#741) · 932bdd93
      Nicolas Patry authored
      # What does this PR do?
      
      
      - Adds Rope NTK scaling.
      
      Done because
      https://github.com/huggingface/text-generation-inference/pull/529 was
      closed
      Took some code from
      https://github.com/huggingface/transformers/pull/24653
      
      - `--rope-scaling` and `--rope-factor` are added separately. I
      considered having a single one and parsing something line ("linear:4.0"
      , or "dynamic") but decided against
      it because it would push more parsing+validation a bit everywhere (both
      in the launcher and the server).
      
      
      Fixes #512
      
      
      
      
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      932bdd93
  21. 24 Jul, 2023 1 commit
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  23. 17 Jul, 2023 2 commits
  24. 14 Jul, 2023 1 commit
  25. 13 Jul, 2023 2 commits
  26. 05 Jul, 2023 1 commit
  27. 01 Jul, 2023 1 commit
  28. 30 Jun, 2023 4 commits
  29. 16 Jun, 2023 1 commit