Instructions to use umiuni/hp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use umiuni/hp with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("umiuni/hp", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| void set_num_threads(int n_threads) | |
| { | |
| omp_set_num_threads(n_threads); | |
| } | |
| int get_num_threads() | |
| { | |
| return omp_get_num_threads(); | |
| } | |
| void compress_int4_weight(void *weight, void *out, int n, int m) | |
| { | |
| for(int i=0;i<n;i++) | |
| { | |
| for(int j=0;j<m;j++) | |
| { | |
| (*(unsigned char*)(out + sizeof(unsigned char) * (i * m + j))) = ((*(unsigned char*)(weight + sizeof(unsigned char) * (i * (m << 1) + (j << 1)))) << 4); | |
| (*(unsigned char*)(out + sizeof(unsigned char) * (i * m + j))) |= (((*(unsigned char*)(weight + sizeof(unsigned char) * (i * (m << 1) + ((j << 1) | 1)))) & 15)); | |
| } | |
| } | |
| } | |
| void extract_int8_weight_to_float(void *weight, void *scale_list, void *out, int n, int m) | |
| { | |
| for(int i=0;i<n;i++) | |
| { | |
| for(int j=0;j<m;j++) | |
| (*(float*)(out + sizeof(float) * (i * m + j))) = (*(float*)(scale_list + sizeof(float) * i)) * (*(char*)(weight + sizeof(char) * (i * m + j))); | |
| } | |
| } | |
| void extract_int4_weight_to_float(void *weight, void *scale_list, void *out, int n, int m) | |
| { | |
| for(int i=0;i<n;i++) | |
| { | |
| for(int j=0;j<m;j++) | |
| { | |
| (*(float*)(out + sizeof(float) * (i * (m << 1) + (j << 1)))) = (*(float*)(scale_list + sizeof(float) * i)) * ((*(char*)(weight + sizeof(char) * (i * m + j))) >> 4); | |
| (*(float*)(out + sizeof(float) * (i * (m << 1) + ((j << 1) | 1)))) = (*(float*)(scale_list + sizeof(float) * i)) * (((char)((*(unsigned char*)(weight + sizeof(char) * (i * m + j))) << 4))>> 4); | |
| } | |
| } | |
| } | |