Phi 3.5 bug fix (#955)
* Update _utils.py * Update _utils.py * Update _utils.py * Update _utils.py * Update _utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * update token retrieval logic (#952) * Fix DPO (#947) * Update _utils.py * Update _utils.py * Update _utils.py * Update _utils.py * Update _utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * update hf token retrieval logic --------- Co-authored-by: Daniel Han <danielhanchen@gmail.com> * Update llama.py * get_token * Update README.md --------- Co-authored-by: Hafedh <70411813+not-lain@users.noreply.github.com>
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Daniel Han
GitHub
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4 changed files with 12 additions and 27 deletions
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@ -32,12 +32,13 @@ All notebooks are **beginner friendly**! Add your dataset, click "Run All", and
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| **DPO Zephyr** | [▶️ Start for free](https://colab.research.google.com/drive/15vttTpzzVXv_tJwEk-hIcQ0S9FcEWvwP?usp=sharing) | 1.9x faster | 43% less |
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- **Kaggle Notebooks** for [Llama 3.1 (8B)](https://www.kaggle.com/danielhanchen/kaggle-llama-3-1-8b-unsloth-notebook), [Gemma 2 (9B)](https://www.kaggle.com/code/danielhanchen/kaggle-gemma-7b-unsloth-notebook/), [Mistral (7B)](https://www.kaggle.com/code/danielhanchen/kaggle-mistral-7b-unsloth-notebook)
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- Run [Llama 3 conversational notebook](https://colab.research.google.com/drive/1XamvWYinY6FOSX9GLvnqSjjsNflxdhNc?usp=sharing) and [Mistral v0.3 ChatML](https://colab.research.google.com/drive/15F1xyn8497_dUbxZP4zWmPZ3PJx1Oymv?usp=sharing)
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- Run [Llama 3.1 conversational notebook](https://colab.research.google.com/drive/15OyFkGoCImV9dSsewU1wa2JuKB4-mDE_?usp=sharing) and [Mistral v0.3 ChatML](https://colab.research.google.com/drive/15F1xyn8497_dUbxZP4zWmPZ3PJx1Oymv?usp=sharing)
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- This [text completion notebook](https://colab.research.google.com/drive/1ef-tab5bhkvWmBOObepl1WgJvfvSzn5Q?usp=sharing) is for continued pretraining / raw text
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- This [continued pretraining notebook](https://colab.research.google.com/drive/1tEd1FrOXWMnCU9UIvdYhs61tkxdMuKZu?usp=sharing) is for learning another language
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- Click [here](https://github.com/unslothai/unsloth/wiki) for detailed documentation for Unsloth.
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## 🦥 Unsloth.ai News
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- 📣 NEW! [Llama 3.1 Conversational notebook](https://colab.research.google.com/drive/15OyFkGoCImV9dSsewU1wa2JuKB4-mDE_?usp=sharing) includes training only on completions / outputs (increase accuracy), ShareGPT standardization and more!
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- 📣 NEW! [Phi-3.5 (mini)](https://colab.research.google.com/drive/1lN6hPQveB_mHSnTOYifygFcrO8C1bxq4?usp=sharing) now supported
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- 📣 NEW! `pip install unsloth` now works! Head over to [pypi](https://pypi.org/project/unsloth/) to check it out! This allows non git pull installs. Use `pip install unsloth[colab-new]` for non dependency installs.
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- 📣 NEW! [Gemma-2-2b](https://colab.research.google.com/drive/1weTpKOjBZxZJ5PQ-Ql8i6ptAY2x-FWVA?usp=sharing) now supported! Try out [Chat interface](https://colab.research.google.com/drive/1i-8ESvtLRGNkkUQQr_-z_rcSAIo9c3lM?usp=sharing)!
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@ -61,6 +61,7 @@ from bitsandbytes.nn import Linear4bit as Bnb_Linear4bit
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from peft.tuners.lora import Linear4bit as Peft_Linear4bit
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from ..save import patch_saving_functions
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import re, os, inspect, math, sys
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from huggingface_hub.utils._token import get_token
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def original_apply_qkv(self, X):
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@ -1263,7 +1264,7 @@ class LongRopeRotaryEmbedding(torch.nn.Module):
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# in FP32. They are applied (multiplied) in FP32 as well.
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self.current_rope_size = seq_len
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t = torch.arange(self.current_rope_size, device=self.inv_freq.device, dtype=torch.int64).float()
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t = torch.arange(self.current_rope_size, device=self.long_inv_freq.device, dtype=torch.int64).float()
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# Long sequences
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freqs = torch.outer(t, self.long_inv_freq)
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emb = torch.cat((freqs, freqs), dim=-1)
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@ -1417,13 +1418,7 @@ class FastLlamaModel:
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"Are you certain you want to do remote code execution?"
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)
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pass
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if token is None and "HF_TOKEN" in os.environ:
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token = os.environ["HF_TOKEN"]
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if token is None and "HUGGINGFACE_TOKEN" in os.environ:
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token = os.environ["HUGGINGFACE_TOKEN"]
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if token is None: token = get_token()
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if model_patcher is None: model_patcher = FastLlamaModel
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SUPPORTS_BFLOAT16 = is_bfloat16_supported()
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gpu_stats = torch.cuda.get_device_properties(0)
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@ -21,6 +21,7 @@ from transformers import __version__ as transformers_version
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from peft import PeftConfig, PeftModel
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from .mapper import INT_TO_FLOAT_MAPPER, FLOAT_TO_INT_MAPPER, MAP_TO_UNSLOTH_16bit
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import os
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from huggingface_hub.utils._token import get_token
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# https://github.com/huggingface/transformers/pull/26037 allows 4 bit loading!
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from packaging.version import Version
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@ -152,12 +153,8 @@ class FastLanguageModel(FastLlamaModel):
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revision = None,
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*args, **kwargs,
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):
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if token is None and "HF_TOKEN" in os.environ:
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token = os.environ["HF_TOKEN"]
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if token is None and "HUGGINGFACE_TOKEN" in os.environ:
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token = os.environ["HUGGINGFACE_TOKEN"]
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if token is None: token = get_token()
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old_model_name = model_name
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model_name = get_model_name(model_name, load_in_4bit)
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@ -29,6 +29,7 @@ import re
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from transformers.models.llama.modeling_llama import logger
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from .tokenizer_utils import fix_sentencepiece_gguf
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from huggingface_hub import HfApi
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from huggingface_hub.utils._token import get_token
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__all__ = [
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"print_quantization_methods",
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@ -207,12 +208,7 @@ def unsloth_save_model(
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temporary_location : str = "_unsloth_temporary_saved_buffers",
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maximum_memory_usage : float = 0.9,
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):
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if token is None and "HF_TOKEN" in os.environ:
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token = os.environ["HF_TOKEN"]
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elif token is None and "hf_token" in os.environ:
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token = os.environ["hf_token"]
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elif token is None and "HUGGINGFACE_TOKEN" in os.environ:
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token = os.environ["HUGGINGFACE_TOKEN"]
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if token is None: token = get_token()
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if commit_message is None: commit_message = ""
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if "Unsloth" not in commit_message:
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@ -1321,12 +1317,8 @@ def create_huggingface_repo(
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token = None,
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private = False,
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):
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if token is None and "HF_TOKEN" in os.environ:
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token = os.environ["HF_TOKEN"]
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elif token is None and "hf_token" in os.environ:
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token = os.environ["hf_token"]
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elif token is None and "HUGGINGFACE_TOKEN" in os.environ:
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token = os.environ["HUGGINGFACE_TOKEN"]
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if token is None :
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token = get_token()
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pass
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save_directory, username = _determine_username(save_directory, "", token)
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