blackmount8
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Upload model and tokenizer.
Browse files- README.md +55 -0
- config.json +6 -0
- model.bin +3 -0
- special_tokens_map.json +24 -0
- tokenizer.model +3 -0
- tokenizer_config.json +34 -0
- vocabulary.json +0 -0
README.md
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---
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license: cc
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---
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---
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license: cc
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datasets:
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- VMware/open-instruct-v1-oasst-dolly-hhrlhf
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language:
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- en
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library_name: transformers
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pipeline_tag: text-generation
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---
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# blackmount8/open-llama-13B-open-instruct-ct2-int8_float16
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Int8_float16version of [VMware/open-llama-13b-open-instruct](https://huggingface.co/VMware/open-llama-13b-open-instruct), quantized using CTranslate2.
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## VMware/open-llama-13B-open-instruct
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Instruction-tuned version of the fully trained Open LLama 13B model. The model is open for `<b>`COMMERCIAL USE `</b>`. `<br>`
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`<b>` NOTE `</b>` : The model was trained using the Alpaca prompt template
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`<b>` NOTE `</b>` : Fast tokenizer results in incorrect encoding, set the ``use_fast = False`` parameter, when instantiating the tokenizer
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## License
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- `<b>`Commercially Viable `</b>`
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- Instruction dataset, [VMware/open-instruct-v1-oasst-dolly-hhrlhf](https://huggingface.co/datasets/VMware/open-instruct-v1-oasst-dolly-hhrlhf) is under cc-by-sa-3.0
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- Language Model, ([openlm-research/open_llama_13b](https://huggingface.co/openlm-research/open_llama_13b)) is under apache-2.0
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## Nomenclature
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- Model : Open-llama
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- Model Size: 13B parameters
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- Dataset: Open-instruct-v1 (oasst, dolly, hhrlhf)
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## Use in CTranslate2
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```
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import ctranslate2
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from transformers import AutoTokenizer
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model_name = "blackmount8/open-llama-13b-open-instruct-ct2-int8_float16"
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tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False, padding_side="left", truncation_side="left")
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model = ctranslate2.Generator(model_name, device="auto", compute_type="int8_float16")
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input_text = ["What is the meaning of stonehenge?", "Hello mate!"]
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input_ids = tokenizer(input_text, return_tensors="pt", padding=True, truncation=True).input_ids
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input_tokens = [tokenizer.convert_ids_to_tokens(ele) for ele in input_ids]
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outputs = model.generate_batch(input_tokens, max_length=128)
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output_tokens = [
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ele.sequences_ids[0] for ele in outputs
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]
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output = tokenizer.batch_decode(output_tokens)
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print(output)
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```
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config.json
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{
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"bos_token": "<s>",
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"eos_token": "</s>",
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"layer_norm_epsilon": null,
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"unk_token": "<unk>"
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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:fdbda702db933751d9e9bfc3b7be138c71c7d9f48f3239c905931f385872e40e
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size 13025087966
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "<unk>",
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:ab1b681ec7fc02fed5edd3026687d7a692a918c4dd8e150ca2e3994a6229843b
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size 534194
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tokenizer_config.json
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{
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"add_bos_token": true,
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"add_eos_token": false,
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"bos_token": {
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"__type": "AddedToken",
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"content": "<s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"clean_up_tokenization_spaces": false,
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"eos_token": {
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"__type": "AddedToken",
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"content": "</s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"model_max_length": 2048,
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"pad_token": null,
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"padding_side": "right",
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"sp_model_kwargs": {},
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": {
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"__type": "AddedToken",
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"content": "<unk>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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vocabulary.json
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