Model Card for Model ID
This model is a fine-tuned version of
teknium/OpenHermes-2.5-Mistral-7B on the argilla/10k_prompts_top_SPIN_iter0 dataset.
WIP:
EXAMPLE:
1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model = AutoModelForCausalLM.from_pretrained("argilla/OpenHermes-2.5-Mistral-7B-top-SPIN-iter0")
4tokenizer = AutoTokenizer.from_pretrained("argilla/OpenHermes-2.5-Mistral-7B-top-SPIN-iter0")
5
6inputs = tokenizer.apply_chat_template(
7 message,
8 add_generation_prompt=True,
9 return_tensors='pt'
10)
11
12tokens = model.generate(
13 inputs.to("cuda"),
14 max_new_tokens=1024,
15 temperature=0.5,
16 do_sample=True
17)
18
19print(tokenizer.decode(tokens[0], skip_special_tokens=False))
Model Details
Model Description
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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Training Details
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Training Procedure
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Training Hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.0
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2
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Environmental Impact
Carbon emissions can be estimated using the
Machine Learning Impact calculator presented in
Lacoste et al. (2019).
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