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Merge pull request #93 from runpod-workers/up-rdme
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Update README.md
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@pandyamarut
pandyamarut authored Aug 5, 2024
2 parents 37d140a + 3498e99 commit 17a2d84
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Expand Up @@ -95,11 +95,12 @@ Below is a summary of the available RunPod Worker images, categorized by image s
| `TOKENIZER` | None | `str` | Name or path of the Hugging Face tokenizer to use. |
| `SKIP_TOKENIZER_INIT` | False | `bool` | Skip initialization of tokenizer and detokenizer. |
| `TOKENIZER_MODE` | 'auto' | ['auto', 'slow'] | The tokenizer mode. |
| `TRUST_REMOTE_CODE` | False | `bool` | Trust remote code from Hugging Face. |
| `TRUST_REMOTE_CODE` | `0` | `bool` as int | Trust remote code from Hugging Face. |
| `DOWNLOAD_DIR` | None | `str` | Directory to download and load the weights. |
| `LOAD_FORMAT` | 'auto' | ['auto', 'pt', 'safetensors', 'npcache', 'dummy', 'tensorizer', 'bitsandbytes'] | The format of the model weights to load. |
| `LOAD_FORMAT` | 'auto' | `str` | The format of the model weights to load. |
| `HF_TOKEN` | - | `str` | Hugging Face token for private and gated models.|
| `DTYPE` | 'auto' | ['auto', 'half', 'float16', 'bfloat16', 'float', 'float32'] | Data type for model weights and activations. |
| `KV_CACHE_DTYPE` | 'auto' | ['auto', 'fp8', 'fp8_e5m2', 'fp8_e4m3'] | Data type for KV cache storage. |
| `KV_CACHE_DTYPE` | 'auto' | ['auto', 'fp8'] | Data type for KV cache storage. |
| `QUANTIZATION_PARAM_PATH` | None | `str` | Path to the JSON file containing the KV cache scaling factors. |
| `MAX_MODEL_LEN` | None | `int` | Model context length. |
| `GUIDED_DECODING_BACKEND` | 'outlines' | ['outlines', 'lm-format-enforcer'] | Which engine will be used for guided decoding by default. |
Expand All @@ -109,26 +110,19 @@ Below is a summary of the available RunPod Worker images, categorized by image s
| `TENSOR_PARALLEL_SIZE` | 1 | `int` | Number of tensor parallel replicas. |
| `MAX_PARALLEL_LOADING_WORKERS` | None | `int` | Load model sequentially in multiple batches. |
| `RAY_WORKERS_USE_NSIGHT` | False | `bool` | If specified, use nsight to profile Ray workers. |
| `BLOCK_SIZE` | 16 | [8, 16, 32] | Token block size for contiguous chunks of tokens. |
| `ENABLE_PREFIX_CACHING` | False | `bool` | Enables automatic prefix caching. |
| `DISABLE_SLIDING_WINDOW` | False | `bool` | Disables sliding window, capping to sliding window size. |
| `USE_V2_BLOCK_MANAGER` | False | `bool` | Use BlockSpaceMangerV2. |
| `NUM_LOOKAHEAD_SLOTS` | 0 | `int` | Experimental scheduling config necessary for speculative decoding. |
| `SEED` | 0 | `int` | Random seed for operations. |
| `SWAP_SPACE` | 4 | `int` | CPU swap space size (GiB) per GPU. |
| `GPU_MEMORY_UTILIZATION` | 0.90 | `float` | The fraction of GPU memory to be used for the model executor. |
| `NUM_GPU_BLOCKS_OVERRIDE` | None | `int` | If specified, ignore GPU profiling result and use this number of GPU blocks. |
| `MAX_NUM_BATCHED_TOKENS` | None | `int` | Maximum number of batched tokens per iteration. |
| `MAX_NUM_SEQS` | 256 | `int` | Maximum number of sequences per iteration. |
| `MAX_LOGPROBS` | 20 | `int` | Max number of log probs to return when logprobs is specified in SamplingParams. |
| `DISABLE_LOG_STATS` | False | `bool` | Disable logging statistics. |
| `QUANTIZATION` | None | [*QUANTIZATION_METHODS, None] | Method used to quantize the weights. |
| `QUANTIZATION` | None | ['awq', 'squeezellm', 'gptq'] | Method used to quantize the weights. |
| `ROPE_SCALING` | None | `dict` | RoPE scaling configuration in JSON format. |
| `ROPE_THETA` | None | `float` | RoPE theta. Use with rope_scaling. |
| `ENFORCE_EAGER` | False | `bool` | Always use eager-mode PyTorch. |
| `MAX_CONTEXT_LEN_TO_CAPTURE` | None | `int` | Maximum context length covered by CUDA graphs. |
| `MAX_SEQ_LEN_TO_CAPTURE` | 8192 | `int` | Maximum sequence length covered by CUDA graphs. |
| `DISABLE_CUSTOM_ALL_REDUCE` | False | `bool` | See ParallelConfig. |
| `TOKENIZER_POOL_SIZE` | 0 | `int` | Size of tokenizer pool to use for asynchronous tokenization. |
| `TOKENIZER_POOL_TYPE` | 'ray' | `str` | Type of tokenizer pool to use for asynchronous tokenization. |
| `TOKENIZER_POOL_EXTRA_CONFIG` | None | `dict` | Extra config for tokenizer pool. |
Expand All @@ -140,7 +134,6 @@ Below is a summary of the available RunPod Worker images, categorized by image s
| `LONG_LORA_SCALING_FACTORS` | None | `tuple` | Specify multiple scaling factors for LoRA adapters. |
| `MAX_CPU_LORAS` | None | `int` | Maximum number of LoRAs to store in CPU memory. |
| `FULLY_SHARDED_LORAS` | False | `bool` | Enable fully sharded LoRA layers. |
| `DEVICE` | 'auto' | ['auto', 'cuda', 'neuron', 'cpu', 'openvino', 'tpu', 'xpu'] | Device type for vLLM execution. |
| `SCHEDULER_DELAY_FACTOR` | 0.0 | `float` | Apply a delay before scheduling next prompt. |
| `ENABLE_CHUNKED_PREFILL` | False | `bool` | Enable chunked prefill requests. |
| `SPECULATIVE_MODEL` | None | `str` | The name of the draft model to be used in speculative decoding. |
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