auto use_more_bits = [](int i_layer, int num_layers) -> bool {
return i_layer < num_layers/8 || i_layer >= 7*num_layers/8 || (i_layer - num_layers/8)%3 == 2;
};
+ const int n_expert = std::max(1, (int)qs.model.hparams.n_expert);
+ auto layer_info = [n_expert] (int i_layer, int n_layer, const char * name) {
+ if (n_expert > 1) {
+ // Believe it or not, "experts" in the FFN of Mixtral-8x7B are not consecutive, but iccasionally randomly
+ // sprinkled in the model. Hence, simply dividing i_ffn_down by n_expert does not work
+ // for getting the current layer as I initially thought, and we need to resort to parsing the
+ // tensor name.
+ n_layer /= n_expert;
+ if (sscanf(name, "blk.%d.", &i_layer) != 1) {
+ throw std::runtime_error(format("Failed to determine layer for tensor %s", name));
+ }
+ if (i_layer < 0 || i_layer >= n_layer) {
+ throw std::runtime_error(format("Bad layer %d for tensor %s. Must be in [0, %d)", i_layer, name, n_layer));
+ }
+ }
+ return std::make_pair(i_layer, n_layer);
+ };
if (name == tn(LLM_TENSOR_OUTPUT, "weight")) {
int nx = tensor->ne[0];
new_type = GGML_TYPE_Q2_K;
}
} else if (name.find("ffn_down") != std::string::npos) {
- const int n_expert = std::max(1, (int)qs.model.hparams.n_expert);
- int i_layer, n_layer;
- if (n_expert == 1) {
- i_layer = qs.i_ffn_down;
- n_layer = qs.n_ffn_down;
- } else {
- // Believe it or not, "experts" in the FFN of Mixtral-8x7B are not consecutive, but iccasionally randomly
- // sprinkled in the model. Hence, simply dividing i_ffn_down by n_expert does not work
- // for getting the current layer as I initially thought, and we need to resort to parsing the
- // tensor name.
- n_layer = qs.n_ffn_down / n_expert;
- if (sscanf(name.c_str(), "blk.%d.ffn_down", &i_layer) != 1) {
- throw std::runtime_error(format("Failed to determine layer for tensor %s", name.c_str()));
- }
- if (i_layer < 0 || i_layer >= n_layer) {
- throw std::runtime_error(format("Bad layer %d for tensor %s. Must be in [0, %d)", i_layer, name.c_str(), n_layer));
- }
- }
+ auto info = layer_info(qs.i_ffn_down, qs.n_ffn_down, name.c_str());
+ int i_layer = info.first, n_layer = info.second;
if (ftype == LLAMA_FTYPE_MOSTLY_Q2_K) new_type = GGML_TYPE_Q3_K;
else if (ftype == LLAMA_FTYPE_MOSTLY_Q2_K_S || ftype == LLAMA_FTYPE_MOSTLY_Q3_K_XS) {
if (i_layer < n_layer/8) new_type = GGML_TYPE_Q4_K;
else if (ftype == LLAMA_FTYPE_MOSTLY_Q5_K_M) new_type = GGML_TYPE_Q6_K;
}
else if (name.find("ffn_gate") != std::string::npos) {
- if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_XS && !use_more_bits(qs.i_ffn_gate, qs.n_ffn_gate)) {
+ auto info = layer_info(qs.i_ffn_gate, qs.n_ffn_gate, name.c_str());
+ int i_layer = info.first, n_layer = info.second;
+ if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_XS && !use_more_bits(i_layer, n_layer)) {
new_type = GGML_TYPE_Q2_K;
}
++qs.i_ffn_gate;
}
else if (name.find("ffn_up") != std::string::npos) {
- if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_XS && !use_more_bits(qs.i_ffn_up, qs.n_ffn_up)) {
+ auto info = layer_info(qs.i_ffn_up, qs.n_ffn_up, name.c_str());
+ int i_layer = info.first, n_layer = info.second;
+ if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_XS && !use_more_bits(i_layer, n_layer)) {
new_type = GGML_TYPE_Q2_K;
}
++qs.i_ffn_up;