diff options
Diffstat (limited to 'llama.cpp')
| -rw-r--r-- | llama.cpp | 21 |
1 files changed, 13 insertions, 8 deletions
@@ -6298,7 +6298,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s // TODO: after the GGUF PR, this likely won't work and needs to be updated static int llama_apply_lora_from_file_internal( - const struct llama_model & model, const char * path_lora, const char * path_base_model, int n_threads + const struct llama_model & model, const char * path_lora, float scale, const char * path_base_model, int n_threads ) { LLAMA_LOG_INFO("%s: applying lora adapter from '%s' - please wait ...\n", __func__, path_lora); @@ -6327,7 +6327,7 @@ static int llama_apply_lora_from_file_internal( int32_t lora_alpha; fin.read((char *) &lora_r, sizeof(lora_r)); fin.read((char *) &lora_alpha, sizeof(lora_alpha)); - float scaling = (float)lora_alpha / (float)lora_r; + float scaling = scale * (float)lora_alpha / (float)lora_r; LLAMA_LOG_INFO("%s: r = %d, alpha = %d, scaling = %.2f\n", __func__, lora_r, lora_alpha, scaling); @@ -6543,9 +6543,10 @@ static int llama_apply_lora_from_file_internal( ggml_set_name(r, "r_cpy"); } - struct ggml_cgraph gf = ggml_build_forward(r); + struct ggml_cgraph * gf = ggml_new_graph(lora_ctx); + ggml_build_forward_expand(gf, r); - ggml_graph_compute_helper(work_buffer, &gf, n_threads); + ggml_graph_compute_helper(work_buffer, gf, n_threads); // we won't need these tensors again, reset the context to save memory ggml_free(lora_ctx); @@ -6926,6 +6927,10 @@ uint64_t llama_model_n_params(const struct llama_model * model) { return nparams; } +struct ggml_tensor * llama_get_model_tensor(struct llama_model * model, const char * name) { + return ggml_get_tensor(model->ctx, name); +} + int llama_model_quantize( const char * fname_inp, const char * fname_out, @@ -6939,18 +6944,18 @@ int llama_model_quantize( } } -int llama_apply_lora_from_file(struct llama_context * ctx, const char * path_lora, const char * path_base_model, int n_threads) { +int llama_apply_lora_from_file(struct llama_context * ctx, const char * path_lora, float scale, const char * path_base_model, int n_threads) { try { - return llama_apply_lora_from_file_internal(ctx->model, path_lora, path_base_model, n_threads); + return llama_apply_lora_from_file_internal(ctx->model, path_lora, scale, path_base_model, n_threads); } catch (const std::exception & err) { LLAMA_LOG_ERROR("%s: failed to apply lora adapter: %s\n", __func__, err.what()); return 1; } } -int llama_model_apply_lora_from_file(const struct llama_model * model, const char * path_lora, const char * path_base_model, int n_threads) { +int llama_model_apply_lora_from_file(const struct llama_model * model, const char * path_lora, float scale, const char * path_base_model, int n_threads) { try { - return llama_apply_lora_from_file_internal(*model, path_lora, path_base_model, n_threads); + return llama_apply_lora_from_file_internal(*model, path_lora, scale, path_base_model, n_threads); } catch (const std::exception & err) { LLAMA_LOG_ERROR("%s: failed to apply lora adapter: %s\n", __func__, err.what()); return 1; |