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Model: 4i-ai/Llama-2-13b-alpaca-es Source: Original Platform
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README.md
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README.md
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---
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license: cc-by-nc-4.0
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datasets:
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- bertin-project/alpaca-spanish
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language:
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- es
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inference: false
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---
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# Model Card for Model ID
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This model is the Llama-2-13b-hf fine-tuned with an adapter on the Spanish Alpaca dataset.
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## Model Details
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### Model Description
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This is a Spanish chat model fine-tuned on a Spanish instruction dataset.
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The model expect a prompt containing the instruction, with an option to add an input (see examples below).
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- **Developed by:** 4i Intelligent Insights
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- **Model type:** Chat model
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- **Language(s) (NLP):** Spanish
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- **License:** cc-by-nc-4.0 (inhereted from the alpaca-spanish dataset),
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- **Finetuned from model :** Llama 2 13B ([license agreement](https://ai.meta.com/resources/models-and-libraries/llama-downloads/))
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## Uses
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The model is intended to be used directly without the need of further fine-tuning.
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## Bias, Risks, and Limitations
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This model inherits the bias, risks, and limitations of its base model, Llama 2, and of the dataset used for fine-tuning.
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Note that the Spanish Alpaca dataset was obtained by translating the original Alpaca dataset. It contains translation errors that may have negatively impacted the fine-tuning of the model.
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## How to Get Started with the Model
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Use the code below to get started with the model for inference. The adapter was directly merged into the original Llama 2 model.
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The following code sample uses 4-bit quantization, you may load the model without it if you have enough VRAM. We show results for hyperparameters that we found work well for this set of prompts.
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```py
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from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig, TrainingArguments, GenerationConfig
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import torch
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model_name = "4i-ai/Llama-2-13b-alpaca-es"
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#Tokenizer
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tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
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def create_and_prepare_model():
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compute_dtype = getattr(torch, "float16")
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bnb_config = BitsAndBytesConfig(
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load_in_4bit=True,
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bnb_4bit_quant_type="nf4",
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bnb_4bit_compute_dtype=compute_dtype,
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bnb_4bit_use_double_quant=True,
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)
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model = AutoModelForCausalLM.from_pretrained(
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model_name, quantization_config=bnb_config, device_map={"": 0}
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)
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return model
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model = create_and_prepare_model()
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def generate(instruction, input=None):
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#Format the prompt to look like the training data
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if input is not None:
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prompt = "### Instruction:\n"+instruction+"\n\n### Input:\n"+input+"\n\n### Response:\n"
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else :
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prompt = "### Instruction:\n"+instruction+"\n\n### Response:\n"
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inputs = tokenizer(prompt, return_tensors="pt")
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input_ids = inputs["input_ids"].cuda()
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generation_output = model.generate(
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input_ids=input_ids,
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repetition_penalty=1.5,
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generation_config=GenerationConfig(temperature=0.1, top_p=0.75, top_k=40, num_beams=20), #hyperparameters for generation
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return_dict_in_generate=True,
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output_scores=True,
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max_new_tokens=150, #maximum tokens generated, increase if you want longer asnwer (up to 2048 - the length of the prompt), generation "looks" slower for longer response
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)
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for seq in generation_output.sequences:
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output = tokenizer.decode(seq, skip_special_tokens=True)
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print(output.split("### Response:")[1].strip())
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generate("Háblame de la superconductividad.")
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print("-----------")
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generate("Encuentra la capital de España.")
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print("-----------")
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generate("Encuentra la capital de Portugal.")
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print("-----------")
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generate("Organiza los números dados en orden ascendente.", "2, 3, 0, 8, 4, 10")
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print("-----------")
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generate("Compila una lista de 5 estados de EE. UU. ubicados en el Oeste.")
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print("-----------")
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generate("Compila una lista de 2 estados de EE. UU. ubicados en el Oeste.")
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print("-----------")
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generate("Compila una lista de 10 estados de EE. UU. ubicados en el Este.")
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print("-----------")
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generate("¿Cuál es el color de una fresa?")
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print("-----------")
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generate("¿Cuál es el color de la siguiente fruta?", "fresa")
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print("-----------")
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```
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Expected output:
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```
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La superconductividad es un fenómeno físico en el que los materiales pueden conducir corrientes eléctricas a bajas temperaturas sin pérdida de energía debido a la resistencia. Los materiales superconductores son capaces de conducir corrientes eléctricas a temperaturas mucho más bajas que los materiales normales. Esto se debe a que los electrones en los materiales superconductores se comportan de manera cooperativa, lo que les permite conducir corrientes eléctricas sin pérdida de energía. Los materiales superconductores tienen muchas aplicaciones
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-----------
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La capital de España es Madrid.
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-----------
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La capital de Portugal es Lisboa.
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-----------
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0, 2, 3, 4, 8, 10
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-----------
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1. California
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2. Oregón
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3. Washington
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4. Nevada
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5. Arizona
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-----------
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California y Washington.
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-----------
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1. Maine
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2. Nuevo Hampshire
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3. Vermont
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4. Massachusetts
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5. Rhode Island
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6. Connecticut
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7. Nueva York
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8. Nueva Jersey
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9. Pensilvania
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10. Delaware
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-----------
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El color de una fresa es rojo brillante.
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-----------
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El color de la fresa es rojo.
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-----------
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```
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## Contact Us
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[4i.ai](https://4i.ai/) provides natural language processing solutions with dialog, vision and voice capabilities to deliver real-life multimodal human-machine conversations.
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Please contact us at info@4i.ai
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config.json
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{
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"_name_or_path": "merged_results_13b/",
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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": 5120,
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"initializer_range": 0.02,
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"intermediate_size": 13824,
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"max_position_embeddings": 4096,
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"model_type": "llama",
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"num_attention_heads": 40,
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"num_hidden_layers": 40,
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"num_key_value_heads": 40,
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"pad_token_id": 0,
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"pretraining_tp": 1,
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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": "float32",
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"transformers_version": "4.31.0",
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"use_cache": true,
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"vocab_size": 32000
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}
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"_from_model_config": true,
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"transformers_version": "4.31.0"
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}
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||||
}
|
||||
24
special_tokens_map.json
Normal file
24
special_tokens_map.json
Normal file
@@ -0,0 +1,24 @@
|
||||
{
|
||||
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|
||||
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||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
}
|
||||
}
|
||||
93423
tokenizer.json
Normal file
93423
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
33
tokenizer_config.json
Normal file
33
tokenizer_config.json
Normal file
@@ -0,0 +1,33 @@
|
||||
{
|
||||
"bos_token": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"pad_token": null,
|
||||
"padding_side": "right",
|
||||
"sp_model_kwargs": {},
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": {
|
||||
"__type": "AddedToken",
|
||||
"content": "<unk>",
|
||||
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|
||||
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|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user