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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]>
46 lines
1.1 KiB
Python
46 lines
1.1 KiB
Python
from mistralrs import (
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Runner,
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Which,
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ChatCompletionRequest,
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Architecture,
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AnyMoeConfig,
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AnyMoeExpertType,
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)
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runner = Runner(
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which=Which.Plain(
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model_id="mistralai/Mistral-7B-Instruct-v0.1",
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arch=Architecture.Mistral,
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),
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anymoe_config=AnyMoeConfig(
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hidden_size=4096,
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dataset_json="examples/amoe.json",
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prefix="model.layers",
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mlp="mlp",
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expert_type=AnyMoeExpertType.LoraAdapter(
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rank=64, alpha=16.0, target_modules=["gate_proj"]
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),
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lr=1e-3,
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epochs=100,
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batch_size=4,
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model_ids=["typeof/zephyr-7b-beta-lora"],
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# For inference (use a pretrained gating layer) see `anymoe_inference.py`
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loss_csv_path="loss.csv",
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),
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)
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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=[
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{"role": "user", "content": "Tell me a story about the Rust type system."}
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],
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max_tokens=256,
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presence_penalty=1.0,
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top_p=0.1,
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temperature=0.1,
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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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