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~ | code styling
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270
g4f/models.py
270
g4f/models.py
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@ -1,8 +1,6 @@
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from dataclasses import dataclass
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from .Provider import Bard, BaseProvider, GetGpt, H2o, Liaobots, Vercel, Equing
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@dataclass
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class Model:
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name: str
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@ -12,214 +10,190 @@ class Model:
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# GPT-3.5 / GPT-4
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gpt_35_turbo = Model(
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name="gpt-3.5-turbo",
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base_provider="openai",
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best_provider=GetGpt,
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)
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name = 'gpt-3.5-turbo',
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base_provider = 'openai',
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best_provider = GetGpt)
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gpt_4 = Model(
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name="gpt-4",
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base_provider="openai",
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best_provider=Liaobots,
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)
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name = 'gpt-4',
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base_provider = 'openai',
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best_provider = Liaobots)
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# Bard
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palm = Model(
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name="palm",
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base_provider="google",
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best_provider=Bard,
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)
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name = 'palm',
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base_provider = 'google',
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best_provider = Bard)
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# H2o
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falcon_7b = Model(
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name="h2oai/h2ogpt-gm-oasst1-en-2048-falcon-7b-v3",
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base_provider="huggingface",
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best_provider=H2o,
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)
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name = 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-7b-v3',
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base_provider = 'huggingface',
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best_provider = H2o)
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falcon_40b = Model(
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name="h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1",
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base_provider="huggingface",
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best_provider=H2o,
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)
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name = 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1',
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base_provider = 'huggingface',
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best_provider = H2o)
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llama_13b = Model(
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name="h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-13b",
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base_provider="huggingface",
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best_provider=H2o,
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)
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name = 'h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-13b',
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base_provider = 'huggingface',
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best_provider = H2o)
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# Vercel
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claude_instant_v1 = Model(
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name="anthropic:claude-instant-v1",
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base_provider="anthropic",
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best_provider=Vercel,
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)
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name = 'anthropic:claude-instant-v1',
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base_provider = 'anthropic',
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best_provider = Vercel)
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claude_v1 = Model(
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name="anthropic:claude-v1",
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base_provider="anthropic",
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best_provider=Vercel,
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)
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name = 'anthropic:claude-v1',
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base_provider = 'anthropic',
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best_provider = Vercel)
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claude_v2 = Model(
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name="anthropic:claude-v2",
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base_provider="anthropic",
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best_provider=Vercel,
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)
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name = 'anthropic:claude-v2',
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base_provider = 'anthropic',
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best_provider = Vercel)
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command_light_nightly = Model(
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name="cohere:command-light-nightly",
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base_provider="cohere",
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best_provider=Vercel,
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)
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name = 'cohere:command-light-nightly',
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base_provider = 'cohere',
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best_provider = Vercel)
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command_nightly = Model(
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name="cohere:command-nightly",
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base_provider="cohere",
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best_provider=Vercel,
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)
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name = 'cohere:command-nightly',
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base_provider = 'cohere',
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best_provider = Vercel)
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gpt_neox_20b = Model(
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name="huggingface:EleutherAI/gpt-neox-20b",
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base_provider="huggingface",
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best_provider=Vercel,
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)
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name = 'huggingface:EleutherAI/gpt-neox-20b',
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base_provider = 'huggingface',
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best_provider = Vercel)
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oasst_sft_1_pythia_12b = Model(
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name="huggingface:OpenAssistant/oasst-sft-1-pythia-12b",
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base_provider="huggingface",
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best_provider=Vercel,
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)
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name = 'huggingface:OpenAssistant/oasst-sft-1-pythia-12b',
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base_provider = 'huggingface',
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best_provider = Vercel)
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oasst_sft_4_pythia_12b_epoch_35 = Model(
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name="huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5",
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base_provider="huggingface",
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best_provider=Vercel,
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)
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name = 'huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5',
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base_provider = 'huggingface',
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best_provider = Vercel)
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santacoder = Model(
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name="huggingface:bigcode/santacoder",
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base_provider="huggingface",
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best_provider=Vercel,
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)
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name = 'huggingface:bigcode/santacoder',
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base_provider = 'huggingface',
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best_provider = Vercel)
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bloom = Model(
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name="huggingface:bigscience/bloom",
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base_provider="huggingface",
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best_provider=Vercel,
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)
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name = 'huggingface:bigscience/bloom',
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base_provider = 'huggingface',
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best_provider = Vercel)
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flan_t5_xxl = Model(
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name="huggingface:google/flan-t5-xxl",
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base_provider="huggingface",
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best_provider=Vercel,
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)
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name = 'huggingface:google/flan-t5-xxl',
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base_provider = 'huggingface',
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best_provider = Vercel)
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code_davinci_002 = Model(
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name="openai:code-davinci-002",
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base_provider="openai",
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best_provider=Vercel,
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)
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name = 'openai:code-davinci-002',
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base_provider = 'openai',
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best_provider = Vercel)
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gpt_35_turbo_16k = Model(
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name="openai:gpt-3.5-turbo-16k",
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base_provider="openai",
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best_provider=Vercel,
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)
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name = 'openai:gpt-3.5-turbo-16k',
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base_provider = 'openai',
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best_provider = Vercel)
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gpt_35_turbo_16k_0613 = Model(
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name="openai:gpt-3.5-turbo-16k-0613",
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base_provider="openai",
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best_provider=Equing,
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)
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name = 'openai:gpt-3.5-turbo-16k-0613',
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base_provider = 'openai',
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best_provider = Equing)
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gpt_4_0613 = Model(
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name="openai:gpt-4-0613",
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base_provider="openai",
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best_provider=Vercel,
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)
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name = 'openai:gpt-4-0613',
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base_provider = 'openai',
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best_provider = Vercel)
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text_ada_001 = Model(
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name="openai:text-ada-001",
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base_provider="openai",
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best_provider=Vercel,
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)
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name = 'openai:text-ada-001',
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base_provider = 'openai',
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best_provider = Vercel)
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text_babbage_001 = Model(
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name="openai:text-babbage-001",
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base_provider="openai",
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best_provider=Vercel,
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)
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name = 'openai:text-babbage-001',
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base_provider = 'openai',
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best_provider = Vercel)
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text_curie_001 = Model(
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name="openai:text-curie-001",
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base_provider="openai",
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best_provider=Vercel,
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)
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name = 'openai:text-curie-001',
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base_provider = 'openai',
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best_provider = Vercel)
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text_davinci_002 = Model(
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name="openai:text-davinci-002",
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base_provider="openai",
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best_provider=Vercel,
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)
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name = 'openai:text-davinci-002',
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base_provider = 'openai',
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best_provider = Vercel)
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text_davinci_003 = Model(
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name="openai:text-davinci-003",
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base_provider="openai",
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best_provider=Vercel,
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)
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name = 'openai:text-davinci-003',
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base_provider = 'openai',
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best_provider = Vercel)
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llama13b_v2_chat = Model(
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name="replicate:a16z-infra/llama13b-v2-chat",
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base_provider="replicate",
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best_provider=Vercel,
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)
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name = 'replicate:a16z-infra/llama13b-v2-chat',
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base_provider = 'replicate',
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best_provider = Vercel)
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llama7b_v2_chat = Model(
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name="replicate:a16z-infra/llama7b-v2-chat",
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base_provider="replicate",
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best_provider=Vercel,
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)
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name = 'replicate:a16z-infra/llama7b-v2-chat',
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base_provider = 'replicate',
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best_provider = Vercel)
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class ModelUtils:
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convert: dict[str, Model] = {
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# GPT-3.5 / GPT-4
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"gpt-3.5-turbo": gpt_35_turbo,
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"gpt-4": gpt_4,
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'gpt-3.5-turbo' : gpt_35_turbo,
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'gpt-4' : gpt_4,
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# Bard
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"palm2": palm,
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"palm": palm,
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"google": palm,
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"google-bard": palm,
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"google-palm": palm,
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"bard": palm,
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'palm2' : palm,
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'palm' : palm,
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'google' : palm,
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'google-bard' : palm,
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'google-palm' : palm,
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'bard' : palm,
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# H2o
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"falcon-40b": falcon_40b,
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"falcon-7b": falcon_7b,
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"llama-13b": llama_13b,
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'falcon-40b' : falcon_40b,
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'falcon-7b' : falcon_7b,
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'llama-13b' : llama_13b,
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# Vercel
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"claude-instant-v1": claude_instant_v1,
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"claude-v1": claude_v1,
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"claude-v2": claude_v2,
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"command-light-nightly": command_light_nightly,
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"command-nightly": command_nightly,
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"gpt-neox-20b": gpt_neox_20b,
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"oasst-sft-1-pythia-12b": oasst_sft_1_pythia_12b,
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"oasst-sft-4-pythia-12b-epoch-3.5": oasst_sft_4_pythia_12b_epoch_35,
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"santacoder": santacoder,
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"bloom": bloom,
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"flan-t5-xxl": flan_t5_xxl,
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"code-davinci-002": code_davinci_002,
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"gpt-3.5-turbo-16k": gpt_35_turbo_16k,
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"gpt-3.5-turbo-16k-0613": gpt_35_turbo_16k_0613,
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"gpt-4-0613": gpt_4_0613,
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"text-ada-001": text_ada_001,
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"text-babbage-001": text_babbage_001,
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"text-curie-001": text_curie_001,
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"text-davinci-002": text_davinci_002,
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"text-davinci-003": text_davinci_003,
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"llama13b-v2-chat": llama13b_v2_chat,
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"llama7b-v2-chat": llama7b_v2_chat,
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}
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'claude-instant-v1' : claude_instant_v1,
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'claude-v1' : claude_v1,
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'claude-v2' : claude_v2,
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'command-nightly' : command_nightly,
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'gpt-neox-20b' : gpt_neox_20b,
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'santacoder' : santacoder,
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'bloom' : bloom,
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'flan-t5-xxl' : flan_t5_xxl,
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'code-davinci-002' : code_davinci_002,
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'gpt-3.5-turbo-16k' : gpt_35_turbo_16k,
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'gpt-4-0613' : gpt_4_0613,
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'text-ada-001' : text_ada_001,
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'text-babbage-001' : text_babbage_001,
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'text-curie-001' : text_curie_001,
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'text-davinci-002' : text_davinci_002,
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'text-davinci-003' : text_davinci_003,
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'llama13b-v2-chat' : llama13b_v2_chat,
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'llama7b-v2-chat' : llama7b_v2_chat,
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'oasst-sft-1-pythia-12b' : oasst_sft_1_pythia_12b,
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'oasst-sft-4-pythia-12b-epoch-3.5' : oasst_sft_4_pythia_12b_epoch_35,
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'command-light-nightly' : command_light_nightly,
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'gpt-3.5-turbo-16k-0613' : gpt_35_turbo_16k_0613,
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}
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