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Small fixes
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@ -47,6 +47,10 @@ Examples:
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* **no_flash_attn**: Disables flash attention. Otherwise, it is automatically used as long as the library is installed.
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* **no_flash_attn**: Disables flash attention. Otherwise, it is automatically used as long as the library is installed.
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* **cache_8bit**: Create a 8-bit precision cache instead of a 16-bit one. This saves VRAM but increases perplexity (I don't know by how much).
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* **cache_8bit**: Create a 8-bit precision cache instead of a 16-bit one. This saves VRAM but increases perplexity (I don't know by how much).
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### ExLlamav2
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The same as ExLlamav2_HF but using the internal samplers of ExLlamav2 instead of the ones in the Transformers library.
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### AutoGPTQ
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### AutoGPTQ
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Loads: GPTQ models.
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Loads: GPTQ models.
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@ -6,6 +6,7 @@
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| llama.cpp | ❌ | ❌ | ❌ | ❌ | use llamacpp_HF |
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| llama.cpp | ❌ | ❌ | ❌ | ❌ | use llamacpp_HF |
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| llamacpp_HF | ❌ | ❌ | ❌ | ❌ | ✅ |
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| llamacpp_HF | ❌ | ❌ | ❌ | ❌ | ✅ |
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| ExLlamav2_HF | ✅ | ✅ | ❌ | ❌ | ✅ |
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| ExLlamav2_HF | ✅ | ✅ | ❌ | ❌ | ✅ |
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| ExLlamav2 | ✅ | ✅ | ❌ | ❌ | use ExLlamav2_HF |
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| AutoGPTQ | ✅ | ❌ | ❌ | ✅ | ✅ |
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| AutoGPTQ | ✅ | ❌ | ❌ | ✅ | ✅ |
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| AutoAWQ | ? | ❌ | ? | ? | ✅ |
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| AutoAWQ | ? | ❌ | ? | ? | ✅ |
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| GPTQ-for-LLaMa | ✅\*\* | ✅\*\*\* | ✅ | ✅ | ✅ |
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| GPTQ-for-LLaMa | ✅\*\* | ✅\*\*\* | ✅ | ✅ | ✅ |
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@ -50,7 +50,6 @@ settings = {
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'prompt_lookup_num_tokens': 0,
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'prompt_lookup_num_tokens': 0,
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'custom_stopping_strings': '',
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'custom_stopping_strings': '',
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'custom_token_bans': '',
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'custom_token_bans': '',
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'sampler_priority': 'temperature,top_k,top_p,typical_p,epsilon_cutoff,eta_cutoff,tfs,top_a,min_p,dynamic_temperature,quadratic_sampling,mirostat',
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'auto_max_new_tokens': False,
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'auto_max_new_tokens': False,
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'ban_eos_token': False,
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'ban_eos_token': False,
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'add_bos_token': True,
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'add_bos_token': True,
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@ -130,7 +129,7 @@ group.add_argument('--numa', action='store_true', help='Activate NUMA task alloc
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group.add_argument('--logits_all', action='store_true', help='Needs to be set for perplexity evaluation to work. Otherwise, ignore it, as it makes prompt processing slower.')
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group.add_argument('--logits_all', action='store_true', help='Needs to be set for perplexity evaluation to work. Otherwise, ignore it, as it makes prompt processing slower.')
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group.add_argument('--no_offload_kqv', action='store_true', help='Do not offload the K, Q, V to the GPU. This saves VRAM but reduces the performance.')
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group.add_argument('--no_offload_kqv', action='store_true', help='Do not offload the K, Q, V to the GPU. This saves VRAM but reduces the performance.')
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group.add_argument('--cache-capacity', type=str, help='Maximum cache capacity (llama-cpp-python). Examples: 2000MiB, 2GiB. When provided without units, bytes will be assumed.')
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group.add_argument('--cache-capacity', type=str, help='Maximum cache capacity (llama-cpp-python). Examples: 2000MiB, 2GiB. When provided without units, bytes will be assumed.')
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group.add_argument('--row_split', action='store_true', help='Split multi-gpu by row instead of layer. Faster on some cards.')
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group.add_argument('--row_split', action='store_true', help='Split the model by rows across GPUs. This may improve multi-gpu performance.')
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# ExLlama
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# ExLlama
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group = parser.add_argument_group('ExLlama')
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group = parser.add_argument_group('ExLlama')
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