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	Update convert-llama-h5-to-gguf.py
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		| @@ -120,7 +120,7 @@ if Path(dir_model + "/tokenizer.model").is_file(): | ||||
|             text = tokenizer.id_to_piece(i).replace("\u2581", " ").encode("utf-8") | ||||
|         score: float = tokenizer.get_score(i) | ||||
|  | ||||
|         tokens.append(str(text)) | ||||
|         tokens.append(text) | ||||
|         scores.append(score) | ||||
|  | ||||
| print("write gguf tokens") | ||||
| @@ -184,6 +184,22 @@ for name in list_vars.keys(): | ||||
|                 name = "layers." + str(i) + ".feed_forward.w3.weight" | ||||
|                 break | ||||
|  | ||||
|     n_dims = len(data.shape) | ||||
|  | ||||
|     # ftype == 0 -> float32, ftype == 1 -> float16 | ||||
|     ftype_cur = 0 | ||||
|     if ftype != 0: | ||||
|         if name.endswith(".weight") and n_dims == 2: | ||||
|             data = data.astype(np.float16) | ||||
|             ftype_cur = 1 | ||||
|         else: | ||||
|             data = data.astype(np.float32) | ||||
|             ftype_cur = 0 | ||||
|     else: | ||||
|         if data.dtype != np.float32: | ||||
|             data = data.astype(np.float32) | ||||
|             ftype_cur = 0 | ||||
|  | ||||
|     gguf_writer.write_tensor_info(name, data) | ||||
|  | ||||
|  | ||||
|   | ||||
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