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https://github.com/nomic-ai/gpt4all
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72 lines
3.3 KiB
C++
72 lines
3.3 KiB
C++
#ifndef LLAMAMODEL_H_I_KNOW_WHAT_I_AM_DOING_WHEN_INCLUDING_THIS_FILE
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#error This file is NOT meant to be included outside of llamamodel.cpp. Doing so is DANGEROUS. Be sure to know what you are doing before proceeding to #define LLAMAMODEL_H_I_KNOW_WHAT_I_AM_DOING_WHEN_INCLUDING_THIS_FILE
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#endif
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#ifndef LLAMAMODEL_H
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#define LLAMAMODEL_H
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#include "llmodel.h"
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#include <functional>
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#include <memory>
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#include <string>
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#include <vector>
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struct LLamaPrivate;
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struct EmbModelSpec;
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class LLamaModel : public LLModel {
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public:
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LLamaModel();
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~LLamaModel();
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bool supportsEmbedding() const override { return m_supportsEmbedding; }
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bool supportsCompletion() const override { return m_supportsCompletion; }
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bool loadModel(const std::string &modelPath, int n_ctx, int ngl) override;
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bool isModelBlacklisted(const std::string &modelPath) const override;
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bool isEmbeddingModel(const std::string &modelPath) const override;
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bool isModelLoaded() const override;
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size_t requiredMem(const std::string &modelPath, int n_ctx, int ngl) override;
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size_t stateSize() const override;
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size_t saveState(uint8_t *dest) const override;
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size_t restoreState(const uint8_t *src) override;
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void setThreadCount(int32_t n_threads) override;
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int32_t threadCount() const override;
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std::vector<GPUDevice> availableGPUDevices(size_t memoryRequired = 0) const override;
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bool initializeGPUDevice(size_t memoryRequired, const std::string &name) const override;
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bool initializeGPUDevice(int device, std::string *unavail_reason = nullptr) const override;
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bool usingGPUDevice() const override;
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const char *backendName() const override;
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const char *gpuDeviceName() const override;
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size_t embeddingSize() const override;
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// user-specified prefix
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void embed(const std::vector<std::string> &texts, float *embeddings, std::optional<std::string> prefix,
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int dimensionality = -1, size_t *tokenCount = nullptr, bool doMean = true, bool atlas = false,
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EmbedCancelCallback *cancelCb = nullptr) override;
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// automatic prefix
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void embed(const std::vector<std::string> &texts, float *embeddings, bool isRetrieval, int dimensionality = -1,
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size_t *tokenCount = nullptr, bool doMean = true, bool atlas = false) override;
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private:
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std::unique_ptr<LLamaPrivate> d_ptr;
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bool m_supportsEmbedding = false;
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bool m_supportsCompletion = false;
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protected:
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std::vector<Token> tokenize(PromptContext &ctx, const std::string &str, bool special) const override;
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std::string tokenToString(Token id) const override;
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Token sampleToken(PromptContext &ctx) const override;
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bool evalTokens(PromptContext &ctx, const std::vector<int32_t> &tokens) const override;
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int32_t contextLength() const override;
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const std::vector<Token> &endTokens() const override;
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bool shouldAddBOS() const override;
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int32_t maxContextLength(std::string const &modelPath) const override;
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int32_t layerCount(std::string const &modelPath) const override;
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void embedInternal(const std::vector<std::string> &texts, float *embeddings, std::string prefix, int dimensionality,
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size_t *tokenCount, bool doMean, bool atlas, EmbedCancelCallback *cancelCb,
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const EmbModelSpec *spec);
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};
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#endif // LLAMAMODEL_H
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