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85dcfbef20
* Add model * Update loader * Fix llama config usage * Docs * Fix config no_rope_layers * Fix tie_word_embeddings default * Add chat template * Embed the chat templates * Fix embedding template * enable_thinking default true * Update examples * XML tools for smollm3 * Add smollm3 docs * Fix openai examples * Clippy --------- Co-authored-by: Eric Buehler <[email protected]>
51 lines
1.4 KiB
Python
51 lines
1.4 KiB
Python
from enum import Enum
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import json
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from typing import List, Optional
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from pydantic import BaseModel, Field
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from mistralrs import Runner, Which, ChatCompletionRequest
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runner = Runner(
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which=Which.Plain(
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model_id="meta-llama/Llama-3.2-3B-Instruct",
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),
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)
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class AirplaneType(str, Enum):
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commercial = "commercial"
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cargo = "cargo"
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private = "private"
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class Airplane(BaseModel):
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id: int = Field(
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..., title="Airplane ID", description="Unique identifier for the airplane"
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)
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model: str = Field(..., title="Model", min_length=1, max_length=100)
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manufacturer: str = Field(..., title="Manufacturer", min_length=1, max_length=100)
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type: AirplaneType = Field(default=AirplaneType.commercial, title="Airplane Type")
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capacity: Optional[int] = Field(None, title="Passenger Capacity", ge=1, le=1000)
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class Fleet(BaseModel):
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fleet_name: str = Field(..., title="Fleet Name", min_length=1, max_length=50)
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airplanes: List[Airplane] = Field(..., title="Fleet Airplanes", min_length=1)
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fleet_schema = Fleet.model_json_schema()
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res = runner.send_chat_completion_request(
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ChatCompletionRequest(
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model="default",
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messages=[{"role": "user", "content": "Give me a sample address."}],
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max_tokens=256,
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temperature=0.1,
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grammar_type="json_schema",
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grammar=json.dumps(fleet_schema),
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)
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)
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print(res.choices[0].message.content)
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print(res.usage)
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