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Model: fierysurf/Ambari-7B-Instruct-v0.1-sharded Source: Original Platform
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*.7z filter=lfs diff=lfs merge=lfs -text
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README.md
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README.md
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---
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license: mit
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language:
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- en
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- kn
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metrics:
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- accuracy
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pipeline_tag: text-generation
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tags:
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- bilingual
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- kannada
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- english
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---
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(This repo contains the sharded version of the [original](https://huggingface.co/Cognitive-Lab/Ambari-7B-base-v0.1) Ambari-7B model)
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# Ambari-7B-Base-v0.1 (sharded)
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## Overview
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Ambari-7B-Base-v0.1 is the first bilingual English/Kannada model in the Ambari series, developed and released by [Cognitivelab.in](https://www.cognitivelab.in/). Based on the Llama2 model by Meta, this 7B parameter model is the outcome of the pretraining stage, involving training on approximately 500 million new Kannada tokens.
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## Usage
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To use the Ambari-7B-Base-v0.1 model, you can follow the example code below:
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```python
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# Usage
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import torch
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from transformers import LlamaTokenizer, LlamaForCausalLM
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model = LlamaForCausalLM.from_pretrained('Cognitive-Lab/Ambari-7B-Base-v0.1')
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tokenizer = LlamaTokenizer.from_pretrained('Cognitive-Lab/Ambari-7B-Base-v0.1')
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prompt = "ಕನ್ನಡದ ಇತಿಹಾಸವನ್ನು ವಿವರವಾಗಿ ತಿಳಿಸಿ"
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inputs = tokenizer(prompt, return_tensors="pt")
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# Generate
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generate_ids = model.generate(inputs.input_ids, max_length=30)
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decoded_output = tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
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print(decoded_output)
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```
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**Important:** The provided model serves as a foundation and is not designed for independent use. We strongly advise conducting finetuning tailored to your particular task(s) of interest before deploying it in a production environment. Feel free to customize the code according to your specific use case, ensuring that the model undergoes finetuning for optimal performance in your desired application.
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config.json
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"_name_or_path": "./llama",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"model_type": "llama",
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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": "4.36.2",
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"use_cache": false,
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"vocab_size": 49600
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}
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30
special_tokens_map.json
Normal file
30
special_tokens_map.json
Normal file
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
130014
tokenizer.json
Normal file
130014
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
3
tokenizer.model
Normal file
3
tokenizer.model
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:02d76a45ce0673e2b1dac635c2b4315ba6e9a778af1a9eab7bf666dbdf1f043b
|
||||
size 994743
|
||||
43
tokenizer_config.json
Normal file
43
tokenizer_config.json
Normal file
@@ -0,0 +1,43 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"bos_token": "<s>",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"legacy": true,
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": "</s>",
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"trust_remote_code": false,
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false,
|
||||
"use_fast": true
|
||||
}
|
||||
Reference in New Issue
Block a user