michaelfeil
commited on
Commit
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483e626
1
Parent(s):
08cdb4c
Upload bigcode/starcoder ctranslate fp16 weights
Browse files- README.md +16 -15
- config.json +41 -4
- model.bin +2 -2
- vocabulary.json +0 -0
README.md
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@@ -264,30 +264,21 @@ Speedup inference while reducing memory by 2x-4x using int8 inference in C++ on
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quantized version of [bigcode/starcoder](https://huggingface.co/bigcode/starcoder)
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```bash
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pip install hf-hub-ctranslate2>=2.0
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```
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Converted on 2023-06-01 using
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```
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ct2-transformers-converter --model bigcode/starcoder --output_dir /home/michael/tmp-ct2fast-starcoder --force --copy_files merges.txt tokenizer.json README.md tokenizer_config.json vocab.json generation_config.json special_tokens_map.json .gitattributes --quantization int8_float16 --trust_remote_code
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```
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Checkpoint compatible to [ctranslate2>=3.14.0](https://github.com/OpenNMT/CTranslate2)
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and [hf-hub-ctranslate2>=2.0.8](https://github.com/michaelfeil/hf-hub-ctranslate2)
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- `compute_type=int8_float16` for `device="cuda"`
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- `compute_type=int8` for `device="cpu"`
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```python
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from
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from transformers import AutoTokenizer
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model_name = "michaelfeil/ct2fast-starcoder"
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model = GeneratorCT2fromHfHub(
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# load in int8 on CUDA
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model_name_or_path=model_name,
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device="cuda",
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compute_type="int8_float16",
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# tokenizer=AutoTokenizer.from_pretrained("
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)
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outputs = model.generate(
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text=["def fibonnaci(", "User: How are you doing? Bot:"],
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print(outputs)
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```
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# Licence and other remarks:
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This is just a quantized version. Licence conditions are intended to be idential to original huggingface repo.
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quantized version of [bigcode/starcoder](https://huggingface.co/bigcode/starcoder)
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```bash
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pip install hf-hub-ctranslate2>=2.12.0 ctranslate2>=3.16.0
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```
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```python
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# from transformers import AutoTokenizer
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model_name = "michaelfeil/ct2fast-starcoder"
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from hf_hub_ctranslate2 import GeneratorCT2fromHfHub
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model = GeneratorCT2fromHfHub(
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# load in int8 on CUDA
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model_name_or_path=model_name,
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device="cuda",
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compute_type="int8_float16",
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# tokenizer=AutoTokenizer.from_pretrained("{ORG}/{NAME}")
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)
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outputs = model.generate(
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text=["def fibonnaci(", "User: How are you doing? Bot:"],
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print(outputs)
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```
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Checkpoint compatible to [ctranslate2>=3.16.0](https://github.com/OpenNMT/CTranslate2)
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and [hf-hub-ctranslate2>=2.12.0](https://github.com/michaelfeil/hf-hub-ctranslate2)
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- `compute_type=int8_float16` for `device="cuda"`
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- `compute_type=int8` for `device="cpu"`
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Converted on 2023-06-27 using
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```
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ct2-transformers-converter --model bigcode/starcoder --output_dir ~/tmp-ct2fast-starcoder --force --copy_files merges.txt tokenizer.json README.md tokenizer_config.json vocab.json generation_config.json special_tokens_map.json .gitattributes --quantization int8_float16 --trust_remote_code
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```
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# Licence and other remarks:
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This is just a quantized version. Licence conditions are intended to be idential to original huggingface repo.
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config.json
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{
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{
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"_name_or_path": "/fsx/bigcode/experiments/pretraining/conversions/starcoderpy/large-model",
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"activation_function": "gelu",
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"architectures": [
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"GPTBigCodeForCausalLM"
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],
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"attention_softmax_in_fp32": true,
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"multi_query": true,
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"attn_pdrop": 0.1,
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"bos_token_id": 0,
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"embd_pdrop": 0.1,
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"eos_token_id": 0,
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"inference_runner": 0,
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"initializer_range": 0.02,
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"layer_norm_epsilon": null,
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"max_batch_size": null,
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"max_sequence_length": null,
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"model_type": "gpt_bigcode",
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"n_embd": 6144,
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"n_head": 48,
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"n_inner": 24576,
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"n_layer": 40,
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"n_positions": 8192,
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"pad_key_length": true,
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"pre_allocate_kv_cache": false,
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"resid_pdrop": 0.1,
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"scale_attention_softmax_in_fp32": true,
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"scale_attn_weights": true,
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"summary_activation": null,
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"summary_first_dropout": 0.1,
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"torch_dtype": "float32",
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"transformers_version": "4.28.1",
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"use_cache": true,
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"validate_runner_input": true,
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"vocab_size": 49152,
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"bos_token": "<|endoftext|>",
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"eos_token": "<|endoftext|>",
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"unk_token": "<|endoftext|>"
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}
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model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:f6ab1ecb43fb0d2e5aafb356836f92bd816e90e4d46297955c12b9a3f8c1c35d
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size 15577671723
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vocabulary.json
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