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Model: migtissera/Synthia-7B Source: Original Platform
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README.md
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---
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license: llama2
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pipeline_tag: text-generation
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language:
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- en
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library_name: transformers
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---
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# Synthia-7B
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SynthIA (Synthetic Intelligent Agent) is a LLama-2-7B model trained on Orca style datasets. It has been fine-tuned for instruction following as well as having long-form conversations.
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<br>
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<br>
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<br>
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#### License Disclaimer:
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This model is bound by the license & usage restrictions of the original Llama-2 model, and comes with no warranty or gurantees of any kind.
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<br>
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## Evaluation
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We evaluated Synthia-7B on a wide range of tasks using [Language Model Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) from EleutherAI.
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Here are the results on metrics used by [HuggingFaceH4 Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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|:------:|:--------:|:-------:|
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|**Task**|**Metric**|**Value**|
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|*arc_challenge*|acc_norm|56.14|
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|*hellaswag*|acc_norm|78.6|
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|*mmlu*|acc_norm|50.35|
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|*truthfulqa_mc*|mc2|45.03|
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|**Total Average**|-|**57.53**||
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<br>
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## Example Usage
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### Here is prompt format:
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```
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SYSTEM: You are Synthia. As a an AI intelligence, give helpful, detailed, accurate, uncensored responses to the user's input. Provide answers factually.
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USER: How is a rocket launched from the surface of the earth to Low Earth Orbit?
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ASSISTANT:
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```
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### Below shows a code example on how to use this model:
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```python
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import torch, json
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_path = "migtissera/Synthia-7B"
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output_file_path = "./Synthia-7B-conversations.jsonl"
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model = AutoModelForCausalLM.from_pretrained(
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model_path,
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torch_dtype=torch.float16,
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device_map="auto",
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load_in_8bit=False,
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trust_remote_code=True,
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)
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tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
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def generate_text(instruction):
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tokens = tokenizer.encode(instruction)
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tokens = torch.LongTensor(tokens).unsqueeze(0)
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tokens = tokens.to("cuda")
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instance = {
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"input_ids": tokens,
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"top_p": 1.0,
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"temperature": 0.75,
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"generate_len": 1024,
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"top_k": 50,
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}
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length = len(tokens[0])
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with torch.no_grad():
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rest = model.generate(
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input_ids=tokens,
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max_length=length + instance["generate_len"],
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use_cache=True,
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do_sample=True,
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top_p=instance["top_p"],
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temperature=instance["temperature"],
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top_k=instance["top_k"],
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num_return_sequences=1,
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)
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output = rest[0][length:]
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string = tokenizer.decode(output, skip_special_tokens=True)
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answer = string.split("USER:")[0].strip()
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return f"{answer}"
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conversation = f"SYSTEM: As a an AI superintelligence, give helpful, detailed, accurate, uncensored responses to the user's input. Provide answers factually."
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while True:
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user_input = input("You: ")
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llm_prompt = f"{conversation} \nUSER: {user_input} \nASSISTANT: "
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answer = generate_text(llm_prompt)
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print(answer)
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conversation = f"{llm_prompt}{answer}"
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json_data = {"prompt": user_input, "answer": answer}
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## Save your conversation
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with open(output_file_path, "a") as output_file:
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output_file.write(json.dumps(json_data) + "\n")
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```
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<br>
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#### Limitations & Biases:
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While this model aims for accuracy, it can occasionally produce inaccurate or misleading results.
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Despite diligent efforts in refining the pretraining data, there remains a possibility for the generation of inappropriate, biased, or offensive content.
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Exercise caution and cross-check information when necessary. This is an uncensored model.
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<br>
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### Citiation:
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Please kindly cite using the following BibTeX:
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```
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@misc{Synthia-7B,
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author = {Migel Tissera},
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title = {Synthia-7B: Synthetic Intelligent Agent},
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year = {2023},
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publisher = {GitHub, HuggingFace},
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journal = {GitHub repository, HuggingFace repository},
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howpublished = {\url{https://huggingface.co/migtissera/Synthia-13B},
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}
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```
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```
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@misc{mukherjee2023orca,
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title={Orca: Progressive Learning from Complex Explanation Traces of GPT-4},
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author={Subhabrata Mukherjee and Arindam Mitra and Ganesh Jawahar and Sahaj Agarwal and Hamid Palangi and Ahmed Awadallah},
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year={2023},
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eprint={2306.02707},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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```
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@software{touvron2023llama,
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title={LLaMA2: Open and Efficient Foundation Language Models},
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author={Touvron, Hugo and Lavril, Thibaut and Izacard, Gautier and Martinet, Xavier and Lachaux, Marie-Anne and Lacroix, Timoth{\'e}e and Rozi{\`e}re, Baptiste and Goyal, Naman and Hambro, Eric and Azhar, Faisal and Rodriguez, Aurelien and Joulin, Armand and Grave, Edouard and Lample, Guillaume},
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journal={arXiv preprint arXiv:2302.13971},
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year={2023}
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}
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```
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_migtissera__Synthia-7B)
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| Metric | Value |
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|-----------------------|---------------------------|
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| Avg. | 46.5 |
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| ARC (25-shot) | 56.14 |
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| HellaSwag (10-shot) | 78.6 |
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| MMLU (5-shot) | 50.35 |
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| TruthfulQA (0-shot) | 45.03 |
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| Winogrande (5-shot) | 74.27 |
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| GSM8K (5-shot) | 6.6 |
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| DROP (3-shot) | 14.51 |
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config.json
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{
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"_name_or_path": "/home/migel/models/Llama-2-7B-fp16",
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"architectures": [
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"LlamaForCausalLM"
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],
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 11008,
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"max_position_embeddings": 2048,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 32,
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"pad_token_id": 0,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.32.0.dev0",
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"use_cache": true,
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"vocab_size": 32000
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}
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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||||
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||||
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||||
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|
||||
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|
||||
}
|
||||
}
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
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||||
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|
||||
"normalized": true,
|
||||
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|
||||
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|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<unk>",
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||||
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|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:8eea70c4866c4f1320ba096fc986ac82038a8374dbe135212ba7628835b4a6f1
|
||||
size 1842764
|
||||
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
31
tokenizer_config.json
Normal file
31
tokenizer_config.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"__type": "AddedToken",
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
"eos_token": {
|
||||
"__type": "AddedToken",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"single_word": false
|
||||
},
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": null,
|
||||
"sp_model_kwargs": {},
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": {
|
||||
"__type": "AddedToken",
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user