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point-alpaca's Issues

How to support you for 13B

Hi there,

How do we support you to train 13B?

13B is coming for sure, larger versions - maybe. Consider supporting us if you want it done faster. :)

Please let me know what all is needed.

encounter exception running chat.py: PytorchStreamReader failed reading zip archive: failed finding central directory

Decryption works fine with no issue.

When running py chat.py, encounter following error:

Loading ./result...
gpu_count 1
The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. 
The tokenizer class you load from this checkpoint is 'LLaMATokenizer'. 
The class this function is called from is 'LlamaTokenizer'.
Loading checkpoint shards:  33%|██████████████████▎                                    | 1/3 [00:07<00:14,  7.28s/it]
Traceback (most recent call last):
  File "/home/dsu/ai/xf/src/transformers/modeling_utils.py", line 415, in load_state_dict
    return torch.load(checkpoint_file, map_location="cpu")
  File "/home/dsu/p3/lib/python3.10/site-packages/torch/serialization.py", line 797, in load
    with _open_zipfile_reader(opened_file) as opened_zipfile:
  File "/home/dsu/p3/lib/python3.10/site-packages/torch/serialization.py", line 283, in __init__
    super().__init__(torch._C.PyTorchFileReader(name_or_buffer))
RuntimeError: PytorchStreamReader failed reading zip archive: failed finding central directory

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/dsu/ai/xf/src/transformers/modeling_utils.py", line 419, in load_state_dict
    if f.read(7) == "version":
  File "/usr/lib/python3.10/codecs.py", line 322, in decode
    (result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x80 in position 128: invalid start byte

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/dsu/ai/palpaca/mychat.py", line 41, in <module>
    load_model("./result")
  File "/home/dsu/ai/palpaca/mychat.py", line 27, in load_model
    model = transformers.LlamaForCausalLM.from_pretrained(
  File "/home/dsu/ai/xf/src/transformers/modeling_utils.py", line 2709, in from_pretrained
    ) = cls._load_pretrained_model(
  File "/home/dsu/ai/xf/src/transformers/modeling_utils.py", line 3023, in _load_pretrained_model
    state_dict = load_state_dict(shard_file)
  File "/home/dsu/ai/xf/src/transformers/modeling_utils.py", line 431, in load_state_dict
    raise OSError(
OSError: Unable to load weights from pytorch checkpoint file for './result/pytorch_model-00002-of-00003.bin' at './result/pytorch_model-00002-of-00003.bin'. If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True.

I'm running with latest transformer 4.28.0.dev0 (pulled the code today), which has LlamaTokenizer, hence is the message I got earlier regarding tokenizer class warning. Tried the specific transfomers in requirements.txt (git+https://github.com/zphang/transformers.git@68d640f7c368bcaaaecfc678f11908ebbd3d6176), got the same error.

torch version: 2.0.0.

Anyone encounters similar issue and suggestion to resolve the issue? Thanks.

Retrain for 13B+

Would it be possible for you guys to do this?

Question about fine-tuning LLaMa

I was wondering if we could fine-tune LLaMa with our own training data and then apply this to transform it into Alpaca and it would work, or would it be better to fine-tune Alpaca directly? Is it possible at all?

Any plans to...?

https://github.com/nomic-ai/gpt4all Any plans to train llama on this dataset? That would be great.

RuntimeError: probability tensor contains either `inf`, `nan` or element < 0 while running on an RTX 3060 12GB, using 8-bit.

After loading the 8bit model I am facing the following issue:

Loading checkpoint shards: 100%|████████████████████████████████████████████████████████████████| 3/3 [00:14<00:00,  [28/1000$
Human: asd

/home/sadmin/miniconda3/envs/pa/lib/python3.10/site-packages/transformers/generation/utils.py:1201: UserWarning: You have modi
fied the pretrained model configuration to control generation. This is a deprecated strategy to control generation and will be
 removed soon, in a future version. Please use a generation configuration file (see https://huggingface.co/docs/transformers/m
ain_classes/text_generation)
  warnings.warn(
Traceback (most recent call last):
  File "/home/sadmin/point-alpaca/chat.py", line 102, in <module>
    go()
  File "/home/sadmin/point-alpaca/chat.py", line 72, in go
    generated_ids = generator(
  File "/home/sadmin/miniconda3/envs/pa/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_contex
t
    return func(*args, **kwargs)
  File "/home/sadmin/miniconda3/envs/pa/lib/python3.10/site-packages/transformers/generation/utils.py", line 1452, in generate
    return self.sample(
  File "/home/sadmin/miniconda3/envs/pa/lib/python3.10/site-packages/transformers/generation/utils.py", line 2504, in sample
    next_tokens = torch.multinomial(probs, num_samples=1).squeeze(1)
RuntimeError: probability tensor contains either `inf`, `nan` or element < 0

What I tried so far:

quantization_config = BitsAndBytesConfig(
    llm_int8_threshold=1.0,
)

as a variable, then

quantization_config=quantization_config to model = transformers.LLaMAForCausalLM.from_pretrained([...]).cuda{}
Also tried to just passllm_int8_threshold=1.0to the loader - both ways it loads the model, but at generation I have another error:

    return self._apply(lambda t: t.cuda(device))
NotImplementedError: Cannot copy out of meta tensor; no data!

Hardware: RTX 3060 12GB, Ryzen 5700X, 24GB RAM

Error: Checksums do not match. The file may be corrupted

I get Error: Checksums do not match. The file may be corrupted when attempting to decrypt the following files

tokenizer_config.json.a5f5efb2240276709a923b1404e08d93cc896fd1bd31fbe173e1e2789ea210ef.enc

and

special_tokens_map.json.4ad09c72922c015ba04f09eabebe38fb34ecb721ca712922c62038eaf2d0bc61.enc

However, I get the correct checksums for the two (encrypted) files above, as well as for consolidated.00.pth. For the other decrypted files, the checksums are also correct.

However, the decrypted files tokenizer_config.json and special_tokens_map.json are empty.

Do you know what might be causing the issue? Thank you in advance.

How can I chat with characters locally?

As listed in https://alpaca.point.space/ by hosting the model myself? For example, if I would like to create a character locally, should I further finetune the model with data from, say Genshin Impact, or I can do this through prompting?

Can you share md5 of the files in encrypted folder?

Running the model on alpaca.cpp

I've got the decrypted model, however I am unable to run chat.py due to insufficient video memory. How would I go about running the model on alpaca.cpp?
Also, a question on size: given that the original 7B model is a single 13.5GB file, how come the decryption process produces 3 files adding up to 27GB? Thanks!

Latest Commit Gives Incorrect Decryption

The decrypt.py file in the latest commit doesn't give the correct decryption according to MD5 checksum. However, commit 9ee0219, which doesn't utilize multiple CPU cores, give the correct decryption.

load_model("./result")

There is a mistake on line 42 of the chat.py file.
It should be load_model("./result")

Error: Checksums do not match. The file may be corrupted.

I saw the closed issue about the same, but I just pulled the repo and used the scripts. I think if a brand new installation returns this problem, it might worth investigating.

Decrypting file encrypted/config.json.caf9cac32580e31af8254f66c5a070741d70b15a651721748189180325b7d5a8.enc with 5 workers
Writing final chunks...
Decryption completed.
Decrypting file encrypted/generation_config.json.c5c8961ed243834883fb4e45e8850d3873d6100fde97817f59d275a90eba269d.enc with 5 workers
Writing final chunks...
Decryption completed.
Decrypting file encrypted/pytorch_model-00001-of-00003.bin.90d2ab95a32aeb9362814d8b86db2af5454baab8ea3aa8230c271d6962abb9db.enc with 5 workers
Writing final chunks...
Error: Checksums do not match. The file may be corrupted.

Question about Alpaca maximum sequence length

LLaMA seems to have a maximum sequence length of 2048 as stated and written in its source code. However I see that's the token config as a maximum sequence length of 512 here. Does Alpaca have a smaller maximum sequence length than LLaMA? Is that possible?

Corrupted Model Weights

Hey,

I am trying to update the 7B model weights. For all weigths, except one, it works fine.

The corrupted one is: pytorch_model-00003-of-00003.bin.72bf4c96aa6b0c7b56b0336791960da9c75de324ea1131ea4bfc20fde41115c8.enc

Any idea why this particular one is not working?

Greetings

Question about random output

First of all, thank you for your work, but when I use it, the same input will encounter different generation results, how to fix this generation?

As shown in the figure, this is the result of several new runs, but the results are completely different.

Decryption on several files with matching md5 fail

Model files are fine but a few of the .json files aren't working.

Decrypting file encrypted/added_tokens.json.75e3ca5df2973756aa612cb17246ef6020a68ff8d94671508987d373642f7a36.enc with 31 workers
Writing final chunks...
Decryption completed.
Decrypting file encrypted/config.json.caf9cac32580e31af8254f66c5a070741d70b15a651721748189180325b7d5a8.enc with 31 workers
Writing final chunks...
Error: Checksums do not match. The file may be corrupted.
Decrypting file encrypted/generation_config.json.c5c8961ed243834883fb4e45e8850d3873d6100fde97817f59d275a90eba269d.enc with 31 workers
Writing final chunks...
Error: Checksums do not match. The file may be corrupted.
Decrypting file encrypted/pytorch_model-00001-of-00003.bin.90d2ab95a32aeb9362814d8b86db2af5454baab8ea3aa8230c271d6962abb9db.enc with 31 workers
Writing final chunks...
Decryption completed.
Decrypting file encrypted/pytorch_model-00002-of-00003.bin.f3c10a4f5c8beafc6667d34557b64ba479e4dde6ef10672287857b329b7e3229.enc with 31 workers
Writing final chunks...
Decryption completed.
Decrypting file encrypted/pytorch_model-00003-of-00003.bin.72bf4c96aa6b0c7b56b0336791960da9c75de324ea1131ea4bfc20fde41115c8.enc with 31 workers
Writing final chunks...
Decryption completed.
Decrypting file encrypted/pytorch_model.bin.index.json.07ca8edea996b6c3274395fdb2b6c9108f2ffdd610ae55e35c126c21a9d535b1.enc with 31 workers
Writing final chunks...
Decryption completed.
Decrypting file encrypted/special_tokens_map.json.4ad09c72922c015ba04f09eabebe38fb34ecb721ca712922c62038eaf2d0bc61.enc with 31 workers
Writing final chunks...
Decryption completed.
Decrypting file encrypted/tokenizer.model.9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347.enc with 31 workers
Writing final chunks...
Decryption completed.
Decrypting file encrypted/tokenizer_config.json.a5f5efb2240276709a923b1404e08d93cc896fd1bd31fbe173e1e2789ea210ef.enc with 31 workers
Writing final chunks...
Decryption completed.
Decrypting file encrypted/trainer_state.json.43964ae247e74f4055fe1cf99a7a16efc3114402a1cd918b3cd9e2ebf2858ca9.enc with 31 workers
Writing final chunks...
Decryption completed.
Decrypting file encrypted/training_args.bin.02f8c3ba14e3c48c05f76880975d7385c878b0e5a0863e352c82f331150d2bd4.enc with 31 workers
Writing final chunks...
Decryption completed.

can the nice team of pointnetwork share some production details ?

Hi,

I think I just got banned from the telegram chat for a hosting related question regarding alpaca. Although it says:
Questions? Feedback? Chat with us in our Telegram community!

Sorry if I misunderstood the purpose of that chat so let me ask my question here again:

Can someone please share some insights on how to host the alpaca the way you did it ? I noticed that it is snappy and I would like to understand how you do it. Stack, optimizations, hardware ? Load balancing, dynamic batching ?

Thanks for any recommendations

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