vicuna-7B-chemical

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Model Details

Model Description

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This model is currently under testing. It can answer some basic chemical questions and is better than the base-sharded model.

Through some chemical reactions, it can clearly understand the reactant and corresponding products. (For most, it is correct😅)

Just have fun testing it, and ask some interesting questions!!

• Developed by: FelixChao
• Shared by [optional]: CleverShovel/vicuna-7b-v1.3-sharded-bf16
• Finetuned from model [optional]: CleverShovel/vicuna-7b-v1.3-sharded-bf16

How to Get Started with the Model

Use the code below to get started with the model.

For Pipeline

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="FelixChao/vicuna-7B-chemical")

For Model_Loading

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("FelixChao/vicuna-7B-chemical")
model = AutoModelForCausalLM.from_pretrained("FelixChao/vicuna-7B-chemical")

Training Details

Training Data

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Training Procedure

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Preprocessing [optional]

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Training Hyperparameters

• Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

Speeds, Sizes, Times [optional]

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Evaluation

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Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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Environmental Impact

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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

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Glossary [optional]

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Model Card Authors [optional]

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